Applied science jobs in LondonCreate job alerts

Position: Senior Machine Learning Engineer Department: Growth & Customer Experience Engineering Reporting to: Technology Manager Location: Bristol/London Hybrid Role: 3 days a week from office & 2 days working from home Full Time / Part Time Role: Full time Ready for a Challenge?\n Welcome to Just Eat Takeaway.com, a leading global online food delivery platform where we empower everyday convenience! Whether it’s a Friday-night feast, a post-gym poke bowl, or grabbing some groceries, our tech platform connects tens of millions of customers with hundreds of thousands of restaurant, grocery, and convenience partners worldwide. About This Role\n We’re on the lookout for a Senior Machine Learning Engineer to join our dynamic cross-functional team. Your mission? To enhance our product algorithmic recommendations and drive innovation within Just Eat Takeaway.com. \n In this role, you’ll: \n\n • Lead the evolution of existing machine learning and AI capabilities across our platform.\n, • Write highly scalable and testable code while mentoring fellow engineers.\n, • Collaborate with a variety of teams, both internal and external, as we embrace inner-sourced development.\n\n At Just Eat Takeaway.com, ownership is key. You’ll take responsibility for your work from discovery to production, ensuring the ongoing reliability and stability of our systems. This is your chance to lead, deliver, and care for cutting-edge ML systems that impact millions of customers daily! Your Key Responsibilities\n\n • Collaborate with Data Scientists, Product Managers, and Backend Engineers to bridge the gap between model development and production systems.\n, • Lead the architectural design of end-to-end ML systems, from data ingestion and training pipelines to real-time inference and monitoring infrastructure.\n, • Transform innovative data science prototypes into robust, scalable, and secure production software.\n, • Drive the adoption of MLOps best practices to accelerate the feedback loop for Data Scientists.\n, • Communicate the complexities of ML systems to both technical and non-technical stakeholders.\n, • Build and maintain a strong network across Data and Engineering organizations.\n, • Lead projects, mentor peers, and advocate for engineering excellence within the data science domain.\nWhat Will You Bring to the Team?\n\n, • Proficiency in Python and a solid understanding of software engineering principles applied to Machine Learning.\n, • Experience designing and operating ML systems in production, including familiarity with serving patterns.\n, • Knowledge of orchestration tools and cloud-native ML platforms.\n, • Ability to influence decision-making regarding infrastructure and tooling.\n, • Strong knowledge of Infrastructure as Code and containerization.\n, • Familiarity with data engineering fundamentals to debug and optimize data flows.\n, • A proactive mindset to automate manual processes and improve the developer experience for Data Scientists.\nAt JET, This Is How We Play\n Our teams forge connections internally and collaborate with some of the best-known brands globally, giving us a truly international impact in a dynamic environment. Fun, fast-paced, and supportive, the JET culture is all about movement, growth, and celebrating every aspect of our JETers. Thanks to them, we stay one step ahead of the competition! Inclusion, Diversity & Belonging\n No matter who you are, what you look like, who you love, or where you come from, you can find your place at Just Eat Takeaway.com. We’re committed to fostering an inclusive culture that encourages diversity of thought and experience, ensuring all employees feel they truly belong and can bring their most colorful selves to work every day. What Else Are We Delivering?\n Curious to learn more about our JETers, culture, or company? Explore our career site for stories, blogs, podcasts, and more insights into life at JET. \n Are You Ready to Join the Team? Apply Now! \n #KF-LI1

If you are a current Jazz employee please apply via the Internal Career site. \n Jazz Pharmaceuticals is a global biopharma company whose purpose is to innovate to transform the lives of patients and their families. We are dedicated to developing life-changing medicines for people with serious diseases — often with limited or no therapeutic options. We have a diverse portfolio of marketed medicines, including leading therapies for sleep disorders and epilepsy, and a growing portfolio of cancer treatments. Our patient-focused and science-driven approach powers pioneering research and development advancements across our robust pipeline of innovative therapeutics in oncology and neuroscience. Jazz is headquartered in Dublin, Ireland with research and development laboratories, manufacturing facilities and employees in multiple countries committed to serving patients worldwide. Please visit www.jazzpharmaceuticals.com for more information. \n Brief Description: \n The Director, Toxicology is accountable for managing the global nonclinical regulatory and investigative toxicology of assigned Jazz portfolio products, and likewise to support his/her reports overseeing those products. They will collaborate with other members of the toxicology group, Early Development non-clinical scientists, and members of Jazz cross-functional matrix teams to support the overall global nonclinical regulatory strategy of Jazz programs, from research to registration and beyond. The Director, Toxicology, reports to the Head of Toxicology. \n Essential Functions \n The eligible candidate is experienced in leading, supporting and managing cross-functional relationships. The Director, Toxicology has the necessary qualifications and experience for designing and conducting/monitoring toxicology studies at external CROs, interpreting and reporting toxicology findings, and enabling timely high-quality study deliverables. \n They will have the necessary experience for representing Toxicology in cross-functional teams supporting drug development programs and conveying Toxicology consensus position, identifying and pre-emptying potential toxicology issues that may slow or derail a program, and propose adequate de-risking strategies to address or circumvent such issues. Experience is also required in evaluating and preparing responses to inquiries from health authorities addressing global nonclinical development issues in support of IND/CTA and NDA/NDS/BLA packages. The individual has the necessary knowledge and experience to contribute to or lead early development cross-functional teams. \n The Director, Toxicology: \n\n • Is a motivated self-starter with excellent management capabilities and is a critical part of an innovative team that supports the company's drug discovery/development effort.\n, • Conceptualizes, develops, revises, and finalizes toxicology (GLP and non-GLP) study designs and reports; drafts nonclinical sections for IND/CTA and NDA/BLA submissions and other regulatory documents (e.g., IB, DSUR, PSUR, etc.) to ensure regulatory compliance.\n, • Manages and monitors nonclinical studies (GLP and non-GLP) at external CROs per Jazz standards and ensures that global regulatory/compliance requirements are met/exceeded.\n, • Critically reviews and edits CRO nonclinical toxicology study reports, analyzes and interprets data, defines PK/PD and PK/Toxicity correlations, partners in PK modeling and parameter estimation, and coordinates reports' finalization with CROs upon internal review and team communication, ensuring consistency with global regulatory and compliance requirements.\n, • Provides critical input on discovery and nonclinical development strategy including peer review of pharmacology/pharmacokinetic protocols, reports, and regulatory content.\n, • Leads and/or participates in cross functional teams as early development expert to ensure proper integration of these activities into overall project plans.\n, • Partners with and provides subject matter expertise to key internal functions (Regulatory, Quality, Clinical, CMC and formulations, Product Quality, Drug safety, Medical affairs) and their external contractors or collaborators.\n, • Contributes to departmental processes such as SOP's, WI's and templates.\n, • Maintains a current understanding of relevant literature and methodology, as well as the scientific literature related to the assigned Jazz pipeline products and R&D projects.\n\n Required Education, Licenses, Knowledge, Skills, and Abilities \n\n • As a minimum, Ph.D. in Toxicology, Pharmacology, Pathology, Biochemistry or Biology with extensive pharmaceutical industry experience in drug development toxicology. Board certification (e.g., DABT, ERT) is highly desirable, or demonstrable board eligibility with the intention to write the board exam.\n, • Extensive experience with small and large molecules with a preference for oncology and CNS indications.\n, • Experience in outsourcing and monitoring toxicology studies, CRO management, and interacting with study directors and other vendors (e.g., consultants) to obtain timely delivery of clear, accurate, and well-written toxicology study reports with defensible data analyses and data interpretation. Capacity to synthesize and communicate complex information. Capacity to propose practical mitigation (de-risking) strategies.\n, • Strong knowledge of FDA, EMA, and ICH guidance documents and GLP regulations.\n, • Required experience in authoring non-clinical elements of major regulatory submissions (INDs, CTAs, BLA/NDAs or sNDAs) and other regulatory documents (e.g., IB, PSUR, DSUR); preparing science-based responses to regulatory questions.\n, • Deep understanding of QA, regulatory, and clinical functions to guide key nonclinical safety assessment activities to support drug candidates' success at all stages of development.\n, • Ability to synthesize, interpret and integrate diverse, multidisciplinary scientific data (e.g., pharmacology, pharmacokinetics, pathology).\n, • Experience in Discovery Toxicology as applicable to early stages (non IND-enabling) drug development would be a plus.\n, • Excellent verbal communication and scientific writing skills as applied to study reports and regulatory documents. Ability to interact effectively and tactfully with a variety of critical audiences within and outside the organization. Sense of urgency.\n, • Enjoys and thrives in a fast-paced, multi-tasked, and hands-on environment.\n\n #LI-SM1 \n #LI-remote \n Jazz Pharmaceuticals is an equal opportunity/affirmative action employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, or any characteristic protected by law. \n FOR US BASED CANDIDATES ONLY \n Jazz Pharmaceuticals, Inc. is committed to fair and equitable compensation practices and we strive to provide employees with total compensation packages that are market competitive. For this role, the full and complete base pay range is: $204,000.00 - $306,000.00 \n Individual compensation paid within this range will depend on many factors, including qualifications, skills, relevant experience, job knowledge, and other pertinent factors. The goal is to ensure fair and competitive compensation aligned with the candidate's expertise and contributions, within the established pay framework and our Total Compensation philosophy. Internal equity considerations will also influence individual base pay decisions. This range will be reviewed on a regular basis. \n At Jazz, your base pay is only one part of your total compensation package. The successful candidate may also be eligible for a discretionary annual cash bonus or incentive compensation (depending on the role), in accordance with the terms of the Company's Global Cash Bonus Plan or Incentive Compensation Plan, as well as discretionary equity grants in accordance with Jazz's Long Term Equity Incentive Plan. \n The successful candidate will also be eligible to participate in various benefits offerings, including, but not limited to, medical, dental and vision insurance, 401k retirement savings plan, and flexible paid vacation. For more information on our Benefits offerings please click here: .

Overview AI is already making a real impact at Chambers and Partners, with solutions running across our editorial, research, product and commercial teams. We’re now looking for an AI Solutions Lead to lead our AI engineering team and help shape the next stage of how we use AI across the business. \n This is a hands-on leadership role for someone who enjoys solving complex technical problems while bringing people, priorities and ideas together. You'll be the most senior technical voice on AI at Chambers, responsible for defining what good looks like in AI engineering: the standards, modelling choices and evaluation discipline the team works to. \n You’ll stay close to the technology while having the opportunity to influence what we build, why we build it and where AI can create the greatest value. Main Duties and Responsibilities \n\n • \n Lead the delivery of multiple AI initiatives, from discovery and scoping through to production and measuring their impact. \n\n\n • \n Set technical direction across AI architecture, model selection, data and retrieval strategies, evaluation and deployment. \n\n\n • \n Design scalable, secure and maintainable AI solutions in partnership with our Technology and Data teams. \n\n\n • \n Lead, mentor and develop our team of AI engineers, creating an environment where people can do their best work. \n\n\n • \n Champion high-quality engineering practices, including code review and safe, structured and streamlined deployment. \n\n\n • \n Work closely with Product, Research, Commercial, Data and Technology teams to turn business challenges into practical AI solutions and manage cross-team dependencies. \n\n\n • \n Advise senior stakeholders on technical options and trade-offs, helping prioritise the opportunities that will create the greatest value. \n\n\n • \n Keep Chambers connected to developments in AI and identify where emerging technologies can be applied in useful and responsible ways. \n\n Why you should apply \n AI is already in production at Chambers - models running live across editorial, research, product and commercial workflows.?The problems are genuinely hard, largely unsolved, and the output reaches a global professional audience that depends on getting it right. \n It's also a role with room in it. You'll line-manage the AI engineering team and own technical direction, but you'll stay close to the code - this isn't a job where you hand the interesting problems to someone else. You'll work directly with senior stakeholders, help decide what we build rather than just how, and because this is a focused team rather than a large one, the decisions you make show up quickly in what ships. \n Chambers is midway through a significant AI transformation. If you want to shape how a category-defining company applies AI - this is the role. \n Skills, Experience & Personal Attributes \n You'll bring a strong applied data science foundation, with the statistical judgement to frame problems, test hypotheses and evaluate whether AI solutions genuinely work. You'll combine this with experience taking ML and GenAI solutions into production and leading technical teams or workstreams. \n You’ll bring: \n Essential \n\n • \n A data science foundation, applied for outcomes: framing the business question, setting baselines, choosing the right metric and delivering measurable results rather than just models. This comes with statistical rigour: experimental design, sound validation, and an instinct for leakage, bias and overfitting in messy real-world data. \n\n\n • \n Strong ML fundamentals across classical ML and deep learning (pandas, scikit-learn, XGBoost or LightGBM, PyTorch), and the judgement to tell when a language model is the wrong tool. \n\n\n • \n A deep understanding of how modern models are built, not only how they're used: transformer architectures, pre-training and post-training methods (SFT, RLHF/DPO) and evaluation methodology. You will have fine-tuned models yourself, for example with the Hugging Face ecosystem (Transformers, PEFT/LoRA, TRL), and can explain from first principles why a system fails. \n\n\n • \n NLP depth on long-form professional text: classification, information extraction, entity resolution, summarisation, embeddings and retrieval. \n\n\n • \n Real-world delivery of modern AI approaches (RAG, fine-tuning, agentic AI and multimodal models) in production workflows. You'll have built on model APIs (e.g. Azure OpenAI, Anthropic, open-weight models) and evaluation tooling, and know when the framework, or the LLM, is unnecessary. \n\n\n • \n Hands-on engineering skills in Python and SQL, taking work from notebook to production to a high standard (testing, CI/CD, containers, infrastructure-as-code), with production experience on Azure, ideally Azure ML and Databricks. You'll work as a peer of the platform engineering teams. \n\n\n • \n Rigour in running AI in production: experiment tracking and model registry (MLflow), evaluation frameworks and regression testing before release, monitoring and data-drift management, LLM observability and model governance. \n\n\n • \n A track record of owning technical decisions across model selection, data and retrieval strategy, evaluation and production deployment, and of contributing AI expertise to solution architecture. \n\n\n • \n Proven leadership of AI, ML or data science teams: hiring, mentoring and growing a team that ships, and moving it from prototype habits to production discipline. You'll run delivery through Scrum or Kanban, adapted for AI work with time-boxed spikes, hypothesis-driven experiments and definitions of done that include evaluation thresholds. \n\n\n • \n The credibility to advise senior stakeholders, translating complex technical trade-offs and statistical findings into clear, commercially grounded decisions, and being plain about what the data does and doesn't support. \n\n\n • \n A pragmatic, delivery-first mindset: you influence what gets built, then make sure it ships. \n\n\n • \n Genuine curiosity about where AI is heading, and the judgement to know which developments actually matter for the business. \n\n Desirable \n\n • \n Experience across the wider Azure AI and data estate, such as AKS, Azure AI Search, Azure OpenAI and Azure Document Intelligence. \n\n <

Company Description Genomics England is a global leader in enabling genomic medicine and research, focused on creating a world where everyone benefits from genomic healthcare. Building on the 100,000 Genomes Project, we support the NHS’s world-first national whole genome sequencing service and run the growing National Genomic Research Library, alongside delivering numerous major genomics initiatives. By connecting research and clinical care at national scale, we enable immediate healthcare benefits and advances for the future. Our mission is to provide the evidence and digital systems so that by 2035 genomics could play a role in up to half of all healthcare interactions, whilst securing the UK’s position as the best place to discover, prove and benefit from genomic innovations. We are accelerating our impact and working with patients, doctors, scientists, government and industry to improve genomic testing, and help researchers access the health data and technology they need to make new medical discoveries and create more effective, targeted medicines for everybody. Behind the Healthcare and Research outcomes, Genomics England delivers through designing, developing and operating complex healthcare software systems. We're on the cusp of big changes with the real prospect of genomics becoming the fabric of everyday healthcare through the lifetime – from birth to old age. Job Description Develop your research study management experience at the heart of genomic research and discovery. The Generate Research Data Service works with internal and external partners to generate or ingest new data that enriches the National Genomic Research Library, supporting a varied portfolio across areas such as rare disease and cancer, involving genomic, multi-omic, bespoke clinical data and emerging sequencing technologies. Within the service, the Study Management Team helps research studies progress from feasibility assessment and set-up through to delivery, bringing together the inputs and activities needed along the way. We are looking for a Research Study Coordinator to join the Study Management Team on a two-year fixed-term contract, providing coordination and operational support for research studies across the Generate Research Data Service. This is an opportunity to gain exposure to different types of research studies and data, work with multidisciplinary teams and develop your research study management experience. Through effective collaboration, stakeholder engagement and accurate documentation, you will support the coordination activities that help studies move forward. You will help maintain the information, actions and tracking that underpin study delivery, working with colleagues across a range of disciplines to support progress against agreed timelines, quality standards and governance requirements. About the role As a Research Study Coordinator in the Study Management Team, you will help keep study information organised and up to date, coordinate and follow up inputs and actions, support meetings and progress reporting, and help maintain visibility of risks, issues and dependencies. You will work with teams across different disciplines, building broader research study management experience as you develop in the role. Everyday responsibilities include: Support the planning, coordination and operational delivery of research studies across the Generate Research Data Service. Support effective working relationships with internal and external stakeholders, acting as a point of contact for selected study enquiries, and coordinating meetings and working groups. Develop and apply a working understanding of research study processes and lifecycle requirements to support the coordination activities, including tracking genomic and bespoke clinical data delivery in line with agreed specifications, timelines and quality standards. Support study feasibility assessment and set-up by coordinating inputs across data, samples, ethics, legal, governance, quality, finance and resourcing. Maintain accurate and up-to-date study documentation, profiles, trackers and records in agreed systems, helping to ensure study information is organised, consistent and easy to access. Coordinate inputs to reports, progress updates and governance materials, ensuring information is accurate, complete and provided within agreed timelines. Support the identification, documentation and tracking of risks, issues and dependencies, escalating where appropriate and following up agreed actions. Coordinate meetings, workshops and away days for the Generate Research Data Service, ensuring actions are captured and followed through. Skills & experience for success: Experience working in a research, scientific, healthcare or similarly complex environment. Strong organisational skills, with the ability to balance multiple activities and priorities and follow through on actions. Clear written and verbal communication skills, with the ability to work effectively with internal and external stakeholders. A careful and consistent approach to maintaining accurate documentation, records, trackers and shared information. The ability to bring together inputs from different teams and coordinate follow-up of actions and dependencies to support the progression of research studies. The ability to identify, document and appropriately escalate risks, issues and dependencies, while delivering high-quality work to agreed timelines. A proactive and collaborative mindset, with curiosity, sound judgement and a willingness to learn, develop and take ownership. Nice to have: Experience supporting the coordination and/or operational delivery of research studies. An understanding of the research study lifecycle and/or research governance. Experience or knowledge in genomics, healthcare, life sciences or clinical research. Experience working across multidisciplinary teams and supporting the organisation and follow-up of actions or information. Experience using digital tools to maintain accurate trackers, documentation and shared information. Qualifications A degree-level qualification in a science subject, or equivalent relevant experience Additional Information Salary from: £35,000 Closing date for applications - Thursday 29th October at midnight, Being an integral part of such a meaningful mission is extremely rewarding in itself, but in order to support our people, we’re continually improving our benefits package. We pride ourselves on investing in our people and supporting them to achieve their career goals, as well as offering a benefits package including: Generous Leave: 30 days’ holiday plus bank holidays, additional leave for long service, and the option to apply for up to 30 days of remote working abroad annually (approval required). Family-Friendly: Blended working arrangements, flexible working, enhanced maternity, paternity and shared parental leave benefits. Pension & Financial: Defined contribution pension (Genomics England double-matches up to 10%, however you can contribute more if you wish), Life Assurance (3x salary), an Electric Vehicle salary sacrifice scheme and a Give As You Earn scheme. Learning & Development: Individual learning budgets, support for training and certifications, and reimbursement for one annual professional subscription (approval required). Recognition & Rewards: Employee recognition programme and referral scheme. Health & Wellbeing: Subsidised gym membership, a free Headspace account, and access to an Employee Assistance Programme, eye tests, flu jabs.Equal opportunities and our commitment to a diverse and inclusive workplace Genomics England is actively committed to providing and supporting an inclusive environment that promotes equity, diversity and inclusion best practice both within our community and in any other area where we have influence. We are proud of our diverse community where everyone can come to work and feel welcomed and treated with respect regardless of any disability, ethnicity, gender, gender identity, religion, sexual orientation, or social background. Genomics England’s policies of non-discrimination and equity and will be applied fairly to all people, regardless of age, disability, gender identity or reassignment, marital or civil partnership status, being pregnant or recently becoming a parent, race, religion or beliefs, sex or sexual orientation, length of service, whether full or part-time or employed under a permanent or a fixed-term contract or any other relevant factor. Genomics England does not tolerate any form of discrimination, harassment, victimisation or bullying at work. Such behaviour undermines our mission and core values and diminishes the dignity, respect and integrity of all parties. Our People policies outline our commitment to inclusivity. We aim to remove barriers in our recruitment processes and to be flexible with our interview processes. Should you require any adjustments that may help you to fully participate in the recruitment process, we encourage you to discuss this with us. Culture We have four key behaviours that represent what we would like Genomics England to feel like and the culture we want to encourage, in order for us to achieve our mission. These behaviours help us all work well together, deliver on our outcomes, celebrate our successes and share feedback with each other. You can read about these and other aspects of our culture here

Coming from a data science background, you are equally comfortable applying proven machine-learning techniques to traditional analytics problems and working with the latest generative AI (large language models, retrieval-augmented generation, and agent-based applications). Deliver classical data sci

Strong experience with MLOps, production ML systems, model lifecycle management, and monitoring. DesiredDeep experience in applied machine learning science — including developing novel algorithms and translating research into deployable, production-grade ML products. Hybrid working arrangements an

Applied knowledge of data science and ML tools across all stages of the data and model lifecycle. Computer Science, Mathematics, Physics, Engineering, or related discipline). Hands-on experience designing, prototyping, productionizing, maintaining, and scaling ML/data science products in complex env

HOURS:36 We are looking for a Senior Applied Engineer, who will take responsibility for this process from initial problem definition through to delivery. Working alongside partner analysts, you will identify which requirements are suitable for automation, design and build analytical tools on the team's data platform, and support their adoption in practice. You will lead the delivery of analytical products, establish effective approaches for turning exploratory analysis into reliable services, mentor less experienced colleagues and support the Lead Applied Engineer with technical leadership where required. You will join the team's founding cohort of engineers, reporting to the Lead Applied Engineer. This is a senior individual-contributor role for someone with strong statistical and engineering judgement, experience of turning analysis into operational tools, and a clear interest in producing work that analysts use in practice. • Work directly with Defence analysts, largely on-site, to understand their requirements and develop analytical tools that fit their working practices., • Identify recurring analytical requests and develop efficient, event-driven processes that update and present results when new data becomes available., • Develop prototypes quickly and, where they demonstrate value, turn them into tested, monitored and deployable services on the team's data platform., • Apply sound statistical and data science judgement, including selecting appropriate methods, understanding their assumptions, and communicating uncertainty clearly to non-specialist users., • Build proportionate analyst-facing interfaces where needed, such as dashboards, notebooks, command-line tools and small web applications, using the data products provided by the team's data engineers., • Help establish and maintain the team's standards for testing, reproducibility and documentation, and support colleagues through technical review and mentoring., • Experience building analytics, data science or data products that were used by non-technical users., • Experience taking exploratory analysis beyond the notebook into something tested, repeatable and deployed, or a clear understanding of what that requires., • Solid Python software engineering: testing, version control, code review, and working within a shared codebase., • Applied statistical and data-science competence: choosing appropriate methods, understanding their assumptions, and communicating results and uncertainty to non-specialists., • Experience working directly with end users to understand and iterate on requirements. This post is offered on a fixed term basis, at an annual salary of £57,000 - £69,000 plus excellent benefits, including flexible working and family friendly policies, Employee-only benefits guide | The Alan Turing Institute We value diversity of background, experience, and perspective, and are proud to be an inclusive employer. We warmly encourage applications from all backgrounds, particularly from groups currently under-represented in our sector. If you feel passionate about this role butdon’tmeet every single requirement, please apply–we recognise that great candidates may bring strengths beyond the criteria listed. £57,000 to £69,000 plus excellent benefits #J-18808-Ljbffr

Meta builds technologies that help people connect, find communities, and grow businesses. Its apps include Facebook, Messenger, Instagram, and WhatsApp. Meta is also developing immersive augmented and virtual reality experiences as part of the next evolution in social technology. *Instagram и Facebook принадлежат компании Meta Platforms Inc., деятельность которой признана экстремистской и запрещена на территории РФ • Lead and drive a complex product area, defining success, prioritizing problems, and identifying strategies in the wider organizational and company context; adapt strategies as learnings and context change Build consensus on prioritizing and realizing significant opportunities, and determine when to start or stop investment Evaluate when AI is the optimal solution, articulating trade-offs, risks, and second-order effects Translate AI capabilities into product visions that create differentiated value Develop and champion AI-native strategies, including comprehensive evaluations and data strategies for continuous improvement Work with cross-functional teams to define product vision and roadmap, drive progress against goals and milestones, resolve blockers, improve team health, and increase team effectiveness Identify opportunities and resolve dependencies by creating shared strategies across adjacent product areas Reimagine workflows using AI tools responsibly to increase team velocity and capability Foster rapid experimentation and learning across the organization Scale responsible AI practices, workflows, and artifacts across product teams Mentor and coach PMs and cross-functional team members on AI-native practices Influence strategy and progress across partner functions, improving collaboration and resolving divergent goals Orchestrate complex execution across workstreams using AI automation and strategic human oversight while maintaining quality and accountability Communicate product strategy and progress clearly to stakeholders Use AI-enabled tools to build products and independently create artifacts to prototype, validate, or ship Interpret research and state-of-the-art learnings to shape product strategy and apply logical reasoning Assess system and architecture trade-offs and their impact on user experience and business outcomes Lead technical discussions with engineering partners Gather and analyze user research and market analysis to inform product decisions and influence the wider product organization Design experiments, interpret results using AI to accelerate analysis, and drive product decisions Define and run evaluations to interpret model outputs, adjust execution based on learnings, and establish evaluation as a product practice across teams, • 8+ Years of relevant industry experience, including at least 3 years in Product Management, • Bachelor’s degree or equivalent; a STEM subject is ideal but not essential, including Computer Science, Engineering, Information Systems, Analytics, Mathematics, Physics, or Applied Sciences, • Experience leading cross-functional product teams across a full product line, including defining product mission and strategy, requirements, coordinating resources from other groups, and driving milestones and goals, • Experience managing a product through its full lifecycle, • Proven ability to significantly improve product performance and team effectiveness, • Extensive experience analyzing large-scale, complex datasets and making data-driven decisions, • Proficiency using AI-enabled tools to build product artifacts, • Experience developing and scaling AI-native strategies, including evaluations and data strategies, across teams, • Experience integrating diverse user requirements and context into a coherent product strategy, • Experience leading and motivating teams and influencing across an organization, • Strong communication skills, with the ability to explain complex technical topics clearly to audiences at all levels, • Experience identifying and hiring talent for an AI-capable cross-functional team, • Будет плюсом: Ongoing AI skill development, such as prompt/context engineering or agent orchestration, and staying current with emerging AI technologies; integrating AI tools to optimize or redesign workflows and deliver measurable impact; implementing responsible and ethical AI practices, such as risk assessment, bias mitigation, and quality and accuracy reviews, • Benefits are offered in addition to base compensation #J-18808-Ljbffr

dunnhumby is the global leader in Customer Data Science, helping the world's most ambitious retailers and brands put the customer at the heart of every decision. With nearly 3,000 experts across Europe, Asia, Africa and the Americas, we partner with iconic businesses like Tesco, Coca-Cola, Meijer, Procter & Gamble and Metro to turn data into growth, innovation and measurable value for their customers. Our Applied Data Science team turns dunnhumby\’s analytical capability into real commercial impact for our clients. Working directly with retailers and brands, we design and deliver the models, algorithms and insights that answer the hardest questions in retail — from personalisation and basket analysis to pricing, promotions and customer loyalty. Every insight we produce is grounded in real customer data and built to make a measurable difference. We\’re looking for a Senior Applied Data Scientist who expects more from their career. This is an opportunity to apply your expertise to distil complex problems into meaningful, actionable insights -leveraging world-first science, cutting-edge machine learning techniques and human creativity to deliver impactful solutions for clients. Joining our Retail Insight team, you\’ll investigate, develop, implement and deploy a range of complex applications and components for our clients in Tesco, working alongside exceptionally talented colleagues who are challenging and rewriting the rules rather than simply following them. We work collaboratively with our client leadership team and with our clients , using all of the tools and techniques available to us to deliver insight and build solutions that are re-usable, scalable and deliver measurable value. You\’ll drive change, shape innovative solutions, and actively redefine how organisations harness data. • Degree in Statistics, Mathematics, Physics, Economics, or a related quantitative field., • Strong programming skills — Python and SQL are essential; PySpark experience is highly advantageous., • Experience with version control tools (e.g. GIT)., • Solid understanding of analytical technologies, tools, and techniques., • Excellent logical thinking and problem‑solving abilities., • Strong communication skills, with the ability to explain complex concepts clearly to non‑technical audiences., • Proven experience in statistical modelling and applying data science solutions to real client problems., • A passion for connecting technical work to real customer outcomes, delivering clear and measurable impact., • Comfortable building new workstreams from the ground up, including defining direction, structure, and stakeholder alignment., • Background in retail analytics is advantageous., • Enjoy balancing technical depth with commercial impact., • Like exploring new analytical approaches and challenging established thinking., • Take ownership of complex problems and see them through to delivery., • Are motivated by helping others develop and succeed. We won\’t just meet your expectations. We\’ll defy them. So you'll enjoy the comprehensive rewards package you'd expect from a leading technology company. But also, a degree of personal flexibility you might not expect. Plus, thoughtful perks, like flexible working hours and your birthday off. And we don\’t just talk about diversity and inclusion. We live it every day – with thriving networks including dh Gender Equality Network, dh Proud, dh Family, dh One, dh Enabled and dh Thrive as the living proof. We want everyone to have the opportunity to shine and perform at your best throughout our recruitment process — please let your recruiter know what adjustments would help. • Healthcare & Protection: Flexible allowance, private medical insurance through Vitality, life assurance, partner life assurance, income protection and critical illness cover., • Pension: Aviva pension scheme with up to 7.5% employer matching., • Wellbeing: Access to the Wellness Hub and confidential employee assistance support services., • Lifestyle Benefits: Car leasing, Cycle to Work scheme, technology purchase options and additional voluntary benefits., • Time Off: Annual holiday allowance, public holidays, the option to purchase additional leave, loyalty days and a birthday day off., • Additional Recognition: Long service awards and Talent Scout referral rewards. At dunnhumby, we value and respect difference and are committed to building an inclusive culture by creating an environment where you can balance a successful career with your commitments and interests outside of work. We believe that you will do your best at work if you have a work / life balance. Some roles lend themselves to flexible options more than others, so if this is important to you please raise this with your recruiter, as we are open to discussing agile working opportunities during the hiring process. At dunnhumby, we utilise our diversity of thought as our competitive edge . We are proud of our diversity and committed to making dunnhumby an even more inclusive place to work that we can be proud of. Our diversity and inclusion work is designed tocultivate a culture of belonging,where every dunnhumbian feels safe to bring their whole self to work, where everyone is welcome and we practice what we preach. We have a full D&I strategy to implement this long-term behaviour change; in addition, we have five employee-led network groups to support colleagues in the areas of gender, sexual orientation, multiculturalism, mental health and wellbeing, and family. #J-18808-Ljbffr

Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. As a member of the Applied AI team at Anthropic, you will be a Forward Deployed Engineer (FDE) who embeds directly with our most strategic customers to drive transformational AI adoption. You will collaborate closely with customer teams to ship advanced AI applications that solve real world business problems. Our FDEs engage with customers to accelerate the adoption of existing products and create new applications built on our models. Working closely with our Post-Sales, Product, and Engineering teams, you'll combine engineering expertise, an understanding of frontier AI applications, and customer-facing skills to understand customer workflows and develop innovative solutions that address complex business challenges while maintaining our high standards for safety and reliability. You will sit at the frontier of enterprise AI deployments and serve as one of our founding FDEs who helps to shape our forward-deployed motion. We expect our FDEs to operate autonomously, thrive under ambiguity, and represent Anthropic at the highest level in customer environments. This is a significant responsibility: you’ll play a key role in championing our mission in the enterprise. • Work within customer systems to build production applications with Claude models, ensuring that these products meet customer requirements., • Deliver technical artifacts for customers like MCP servers, sub-agents, and agent skills that will be used in production workflows., • Provide white glove deployment support for Anthropic products in enterprise environments., • Identify and codify repeatable deployment patterns and contribute insights back to our Product and Engineering teams., • Maintain strong knowledge of the latest developments in LLM capabilities, implementation patterns, and AI product development stacks., • Build long term relationships with customers and proactively identify new opportunities for AI deployment throughout the lifecycle of an engagement., • Travel frequently (25-50%) to customer sites to build in person with customers., • Be a champion for Anthropic’s mission in the field., • 4+ years of experience in a technical, customer facing role such as Forward Deployed Engineer, or as a Software Engineer with consulting or product experience. Former technical founders are also encouraged to apply., • Production experience with LLMs including advanced prompt engineering, agent development, evaluation frameworks, and deployment at scale., • Strong programming skills with proficiency in Python (and ideally in one or more additional languages like TypeScript, Java, etc) and experience shipping production applications, • High agency with an ability to navigate ambiguity present in complex organizations., • High cooperation mindset for cross-organizational collaboration, balancing competing priorities with integrity., • Passion for advancing safe, beneficial AI systems through creative technical applications., • Strong communication skills to conduct discovery with customers and to convey technical concepts to diverse stakeholders while maintaining a low ego and collaborative approach., • A background in financial services, healthcare/life sciences, or another enterprise vertical is a plus., • Experience with enterprise IT systems and/or AI deployment patterns is a plus. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. £225,000—£255,000 GBP • Minimum education: Bachelor's degree or an equivalent combination of education, training, and/or experience, • Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience, • Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position, • Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices., • Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Learn about our policy for using AI in our application process. #J-18808-Ljbffr

Wholesale is a $50 trillion market still working the way it did in 1950. 90% of transactions happen offline, over calls, catalogues and trade shows, and a product passes through four or five layers of distributors and wholesalers before it reaches a store, with every party deciding on a fraction of the picture. By the time it hits the shelf, it costs roughly 40% more than the maker charged. That inefficiency tax runs into the trillions, and everyone pays it every time they buy anything. Qogita is building the operating system that replaces that chain: a single order book connecting the global market, the rails to move goods across borders, and a self-learning system that does every job once, against real-time data about the whole market. That puts data science at the core of the product. Forecasting reads what is actually selling in every market as it sells, a buyer’s basket is assembled from every available seller and split across the optimal combination, and every trade writes a record that sharpens the next price, allocation and route. It is a hard problem, spanning physical goods, thirty national regimes in Europe alone and buyers who are increasingly agents, and it is already working: 95% of transactions involve no human touch, and the business is doubling every year. You're a data scientist with strong quantitative and ML chops who can move between classical modelling, experimentation, and modern applied ML (including LLMs where they're the right tool). You'll own end-to-end data science work across Qogita's wholesale marketplace: framing ambiguous commercial problems, building models that ship, and keeping them healthy in production. The Data Science team partners with Product, Engineering, Finance, and Commercial to build the intelligence layer behind pricing, matching, demand, and product discovery. • Build and deliver data science solutions across the stack: predictive models, ranking, demand forecasting, segmentation, pricing, experimentation, and LLM-powered features, depending on where the business need is greatest, • Take ownership of business-critical ML systems end-to-end: problem framing, model design, deployment, monitoring, and ongoing maintenance in production, • Translate ambiguous business problems into tractable ML or statistical problems with clear success criteria, working closely with Product and Commercial, • Apply quantitative methods (regression, causal inference, classical ML, and deep learning where useful) to pricing, demand, liquidity, supplier matching, catalogue enrichment, and related marketplace problems, • Design and analyse experiments and A/B tests, owning statistical validity and turning results into recommendations teams can act on, • Collaborate with Engineers to ship models via reproducible MLOps workflows: experiment tracking, model serving, alerting, and production monitoring, • Communicate model choices, limitations, and trade-offs clearly to both engineers and non-technical stakeholders, • 3+ years as a data scientist, applied ML engineer, or quantitative analyst, with meaningful exposure across ML methods and statistical modelling, • A track record of owning models in production, not just building them: maintaining, monitoring, and iterating as live infrastructure, • Solid grounding in ML and stats fundamentals: probability, supervised and unsupervised learning, and measurement/validation discipline, • Strong Python and SQL; comfortable with large transactional datasets and common DS/ML libraries (e.g. pandas, scikit-learn, XGBoost, PyTorch or similar), • Experience collaborating on MLOps-style workflows (experiment tracking, serving, monitoring) and shipping with engineers, • Able to communicate uncertainty and model limitations clearly to technical and non-technical audiences, • Bachelor's or Master's in a quantitative field (Data Science, Statistics, Economics, Econometrics, Mathematics, CS, or related), or equivalent experience, • Pricing and market economics: price theory, buyer behaviour, demand estimation, causal inference, experimentation with real commercial stakes, • Production LLM systems: RAG, evaluation frameworks, prompt/fine-tuning trade-offs, transformers and major model families, LangChain or similar, • Marketplace or B2B dynamics; AWS/GCP/Azure ML infra; Airflow, Docker, dbt, Snowflake, Lightdash or similar #J-18808-Ljbffr

You'll design and deliver the data pipelines, platforms and AI applications that drive our clients' decision-making, working directly with them to turn business questions into production-ready systems on Google Cloud. Our clients span different industries and sizes, from some of the world's biggest brands to fast-growing smaller businesses. We give engineers real technical ownership. You'll be the technical lead on your own projects and client accounts, trusted to make the calls and own the outcome. You'll also be part of an engineering team that reviews each other's work and pitches in across projects. On your accounts, you'll work day to day with fifty-five's consultants and data scientists. You'll combine strong SQL, Python and cloud engineering with sound technical judgement, using AI tools to build faster and to a higher standard while keeping full ownership of what you deliver. You'll also build AI applications for clients and for fifty-five's own teams, and help shape what we offer in data and AI. • Design, build and operate scalable data pipelines, data models and end-to-end solution architectures on GCP (BigQuery, Python, dbt, Airflow, Dataform), balancing reliability, maintainability, performance and cost., • Own technical delivery on your projects and accounts, from scoping to production: making the design decisions, managing risks and dependencies, and communicating trade-offs clearly., • Own the quality of what we deliver, with rigorous validation, automated testing, observability and data-quality controls built into production pipelines, and lead the diagnosis and fix when production issues come up., • Design and build AI applications for clients and for fifty-five, such as LLM agents on Google Cloud with Gemini and Google's ADK. Take them from prototype to production, with evaluation, cost control and secure handling of client data., • Use agentic coding tools such as Claude Code or Codex to build faster and improve testing, checking their output critically and staying accountable for the result. Share what works with the team as demos, docs and reusable patterns., • Work with clients, consulting and data science teams to clarify requirements, challenge assumptions and turn business needs into pragmatic designs, and explain your reasoning to technical and non-technical people., • Raise the team's engineering standards through design and code reviews, strong testing practices and clear documentation., • Excellent SQL and strong Python skills., • Proven experience designing, building and operating reliable data pipelines, data models and cloud platforms (GCP preferred, AWS or Azure also welcome), with transformation and orchestration tooling such as dbt, Airflow or Dataform., • Strong software engineering practices: Git-based workflows, code review, automated testing and CI/CD., • Hands-on experience building with LLMs (Gemini or similar), such as agents, connecting models to data and APIs, and evaluating outputs. The judgement to know when to rely on AI-assisted engineering tools and when to verify., • The ability to break down ambiguous problems, see the business challenge behind a task, make well-reasoned decisions, and prototype and pitch ideas for what we could build for clients., • Excellent client-facing communication and confidence leading delivery independently: running several client projects at once and re-prioritising as client needs change, solo or within a larger project team., • Infrastructure as code (Terraform), cloud IAM, and secure handling of client data., • Taking LLM agents to production: evaluation and guardrails, cost control, or making them available in Slack, Teams or similar tools., • Applied data science (exploratory or statistical analysis), and dashboarding tools such as Looker or Power BI., • Marketing platforms and an understanding of marketing data. Part of The Brandtech Group, fifty-five is a data company helping brands collect, analyse and activate their data across paid, earned and owned channels to increase their marketing ROI and improve customer acquisition and retention. Headquartered in Paris with offices in London, Hong Kong, New York and Shanghai, fifty-five is a certified Google Partner company and was named by Deloitte as one of the fastest-growing tech firms in Europe, thanks to its unique technology approach combining talent with software and service expertise. In return, we are pleased to offer you the following benefits: • Being part of a multicultural, dynamic and fast-growing team, • Continuous (and certified) training on the digital ecosystem and technologies (initial training for all new employees, followed by recurring training sessions), • Private medical coverage through AXA, • Transport for London monthly travel card allowance, • The flexibility to work remotely for part of the week, • 25 days holiday per year, in addition to UK bank and public holidays, • Company pension plan, • Company-sponsored sporting and social activities, • Monthly Codecademy subscription - reimbursable upon completion of chosen training path fifty-five encourages diversity and is committed to guaranteeing equal treatment of all applications, regardless of gender, age, origin, sexual orientation, state of health or political or religious opinion. #J-18808-Ljbffr

Isomorphic Labs (IsoLabs) was launched in 2021 to advance human health by building on and beyond the Nobel‑winning AlphaFold system. Since then, our interdisciplinary team of drug discovery experts and machine learning specialists has built powerful new predictive and generative AI models that accelerate scientific discovery at digital speed. Our name comes from the belief that there is an underlying symmetry between biology and information science. By harnessing AI’s powerful capabilities, we can model complex biological phenomena to help design novel molecules, anticipate how drugs will perform and develop innovative medicines to treat and cure some of the world’s most devastating diseases. We have built a world‑leading drug design engine comprising AI models that are capable of working across multiple therapeutic areas and drug modalities. We are continually innovating on model architecture and developing cutting‑edge capabilities to advance rational drug design. Every day, and with each new breakthrough, we’re getting closer to the promise of digital biology, and achieving our ambitious mission to one day solve all disease with the help of AI. We are looking for Research Engineers with different levels of experience—from Mid through to Senior, Staff, Principal or equivalent levels. This is an exciting opportunity for you to contribute to frontier research at the intersection of AI and drug design. Working in a highly creative, iterative environment, you will partner with scientists and engineers to advance foundational models that will transform the biopharmaceutical world as we know it. You will draw upon your existing engineering and machine‑learning experience while learning from those around you, applying novel techniques and ideas to newly encountered computational biology and chemistry problems. Translate research concepts into practical implementations by developing and optimising state‑of‑the‑art AI models, and building and maintaining robust codebases, data pipelines, and infrastructure for training and evaluation. Design, implement, and run experiments to evaluate the performance and robustness of ML models, using a full spectrum of state‑of‑the‑art machine‑learning methods. Evaluate, tune, and maintain AI/ML models (which includes collecting and preparing data as needed). • Implement algorithms and software to analyse and evaluate the performance of AI models., • Optimise performance of AI/ML models such as Diffusion models, Transformers, GNNs, leveraging a deep understanding of the AI/ML hardware+software stack., • Advise on how to bring AI/ML models to production and/or integrate them into product offerings, and monitor and refine their behavior., • Develop specialised tools/frameworks/infrastructure to aid in the work above. Work closely with research scientists and engineers, contributing to team discussions, sharing knowledge, and actively participating in code reviews to foster a collaborative environment. Proactively identify and address technical challenges, stay updated on the latest AI advancements, and focus on developing solutions that enable scaling our wider foundation and applied model platforms. Execute on independent engineering projects and software development toward research goals. • PhD in a technical subject with major engineering component and exposure to AI/ML, or BSc, MSc and 2+ years of specific experience working on ML model development., • Strong general engineering experience, as evidenced by exposure to one or more of:, • Software design / algorithms, especially for deep learning frameworks, • Modern ML frameworks such as JAX, PyTorch or TensorFlow, • Distributed systems and runtimes, • Compilers (e.g., XLA, Triton, CUDA, Pallas, …), • Large‑scale model training and serving infrastructure, • Experience in navigating complex research codebases, • Databases and data processing pipelines, • Numerical methods, simulation, optimisation, • Strong fundamentals in mathematics, statistics, linear algebra, • Experience with the full ML research and development lifecycle., • Strong understanding of ML theory and applications., • Strong understanding of data structures and algorithms., • Interest in chemistry and biology., • Experience working with biomedical data., • Knowledge of the pharmaceutical industry, ideally with a focus on drug discovery. We are guided by our shared values. It’s not about finding people who think and act in the same way. These values help to guide our work and will continue to strengthen it. • Thoughtful – Curiosity, creativity and care. It is about good people doing good, rigorous and future‑making science every single day., • Brave – Fearlessness, but also initiative and integrity. The scale of the challenge demands nothing less., • Determined – Confidence in our hypothesis, as well as the urgency and agility needed to deliver on it. Because disease won’t wait, so neither should we., • Together – Connection, collaboration across fields and catalytic relationships. It’s knowing that transformation is a group project, and remembering that what we’re doing will have a real impact on real people everywhere., • Creating An Extraordinary Company – We believe that to be successful we need a team with a range of skills and talents. We’re building an environment where collaboration is fundamental, learning is shared and every employee feels supported and able to thrive. We value unique experiences, knowledge, backgrounds, and perspectives, and harness these qualities to create extraordinary impact. It’s hugely important for us to share knowledge and build strong relationships with each other, and we find it easier to do this if we spend time together in person. This is why we follow a hybrid model, and would require you to be able to come into the office 3 days a week (currently Tuesday, Wednesday, and one other day depending on which team you’re in). If you have additional needs that would prevent you from following this hybrid approach, we’d be happy to talk through these if you’re selected for an initial screening call. We are committed to equal employment opportunities regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy or related condition (including breastfeeding) or any other basis protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know. #J-18808-Ljbffr

Senior Research HPC Engineer (LMS 2914) Salary £57, 623 - £61,622 plus London Allowance £5,560 per annum Higher salary of £61,622 - £67,693 plus London Allowance of £5,560 per annum will be available for candidates with significant relevant experience Permanent | Full Time | Location: Hammersmith London • Meet regularly with Heads of IT and Bioinformatics, and other parties to develop and deliver Scientific Computing infrastructure, software provisions, and resilient services in line with strategic and scientific goals, • Work closely with researchers to develop reusable tools and to translate experimental and analytical requirements into scalable computational solutions that accelerate scientific discovery and improve research productivity, • Support researchers in utilising HPC, including triaging user issues and translating common pain points into platform improvements, • Help build and maintain reproducible runtime environments, container images, and workflow-supporting services for scientific computing workloads, including bioinformatics, AI/ML, data processing, and simulation workflows, • Assume responsibility for coordination and provision of HPC user training and onboarding, • Ensure best practices in project management are maintained to ensure work is aligned with defined goals and that HPC projects are managed within agreed benefit, timescale, cost, quality, and risk limits, • Monitor, report on, and promote the Institute’s Scientific Computing provisions, • Design and manage varied communication strategies for effective and timely stakeholder engagement, including user-group meetings to ensure full visibility of their ongoing and future requirements, • Develop and deliver training, documentation (e.g., runbooks, SOPs), and onboarding materials to empower researchers to effectively use computational tools, • Maximise opportunities to network with similar organisations to benchmark services and activities Research developing trends to ensure future provision and cost‑effective delivery of the Institute’s scientific goals, • Assist with the scoping, provisioning, configuration, scaling, and validation of compute, storage, networking, and platform services within a high‑performance computing infrastructure, • Support and implement the packaging, versioning, and validation of scientific software to ensure reproducibility and portability across research projects, • Establish policies and systems to ensure that workloads placed on the HPC systems are managed, prioritised, and run to achieve optimal service levels and uptime, • Install, configure, and manage Linux applications manually and using deployment software, • Resolve workflow performance issues on the cluster, and help to design HPC jobs, • Implement and maintain management and monitoring tools, report usage levels and service level data, • Streamline and automate maintenance, deployment, and configuration tasks, • Alongside the Head of IT, assume responsibility for documenting and implementing relevant disaster recovery processes, • Ensure awareness via user feedback and monitoring of likely points of failure, proactive maintenance in mitigation, and repair of HPC resources by diagnosing, anticipating, and troubleshooting arising problems, • Maintain awareness of emerging HPC software security vulnerabilities and apply relevant security patches, • Support the Head of IT in implementing and maintaining HPC related usage policies, • Support LMS IT staff as requested for issues and queries relating to standalone Linux/Unix systems, • Other duties commensurate with the grade of the post as directed by the supervisor, • A degree in a computing/scientific research/engineering subject with a significant computational component, or equivalent skills and experience. Significant experience of working at a high‑level within a relevant area, • Industry‑standard Linux certifications (e.g. RHCA, RHCSA), • Current qualifications in project management (e.g. PRINCE2), • Knowledge, experience, or qualification in cloud computing, • Knowledge or education to a higher level within a scientific field, • Hands‑on experience supporting and administering Linux‑based systems in an HPC, research, academic, or production environment, • Experience in configuration and maintenance of multi‑queue job scheduling systems (e.g. SLURM), • Experience in the use of scientific software compilation and deployment systems (e.g. Spack, EasyBuild, Lmod, conda), • Virtualisation and containerisation deployment and management (e.g. Docker, Singularity), • Ability to work closely with multidisciplinary research teams, understand scientific computing needs, and deliver practical services that advance scientific goals, • Knowledge of scripting (e.g., Bash) and version control systems (e.g., Git/GitHub) to support reproducible and collaborative research, • Integration of heterogeneous Linux/Windows/Mac environments (e.g. Active Directory), • Ability to troubleshoot issues across systems, networking, storage, identity, containers, schedulers, and user workloads, and to follow problems through to a reliable operational fix, • Experience with automation tooling (e.g. Salt, xCAT), • Maintain awareness of HPC cyber security principles, best practices, and emerging threats, • High attention to detail and accuracy to effectively analyse and interpret complex data and use it solve to complex technical problems quickly and effectively though leadership, delegation and the ability to deep‑dive when necessary, • Exposure to computational research involving GPU, including AI/ML methods applied to biomedical problems, • Experience supporting GPU‑accelerated workloads, NVIDIA tooling, CUDA‑aware environments, and/or AI/ML and bioinformatics workloads on shared compute platforms., • Familiarity with bioinformatics or scientific workflow frameworks (e.g., Nextflow, Snakemake, WDL/Cromwell), and an understanding of reproducible pipeline design, • Experience working in a scientific, academic, life‑science, or research computing environment where requirements evolve through close collaboration with researchers, • Knowledge of tools that support reproducible research and automation (e.g., CI/CD pipelines, workflow testing, IaC tools like Ansible and Terraform), • Familiarity with large‑scale biological data types (e.g., from genomics, EM or confocal microscopy, medical imaging, phenomics) and associated storage/access challenges, • Familiarity with identity, access, and security controls in Linux or research environments, least‑privilege access, and security patching., • Experience of C, R, or Python programming, • Experience with GPU‑focused hardware and software, • Experience monitoring and optimising research workloads and system performance, using tools such as Grafana, Prometheus, Arbiter2, • Motivating and developing staff to utilise HPC effectively through HPC onboarding and training, • Project managing work packages within and between groups, • Resolving complaints and in conflict resolution, • Excellent verbal and written communication skills, • Able to self‑motivate when working independently, on projects, and collaboratively within a team, • Effectively plans, multitask, and prioritises workload to achieve results, adapting quickly while maintaining control in challenging situations, • Ensures appropriate engagement of colleagues with relevant stakeholders and issues, • Ability to develop and encourage cross‑boundary working relationships and to work collaboratively, • Contribute positively to IT and cross‑functional teams and shares knowledge and skills Please note that final appointment will be subject to pre‑employment screening. Please note that applications may be reviewed by both LMS and Imperial staff Closing date: 18 October2026 #J-18808-Ljbffr

We are seeking a highly skilled, motivated and proactive ML Research Engineer to join our dynamic team. In this role, you will be responsible for building and optimizing complex simulation environments to facilitate the training of machine learning models. The ideal candidate will have a strong background in programming, modelling and machine learning, with optional expertise in reinforcement learning. Aeris-UK is an applied AI company working on real-world problems that require creativity, rigour and solid engineering. We build machine learning systems that are efficient, understandable and ready to operate in the complexity of real environments, whether that involves supporting infrastructure resilience, enabling autonomous decision‑making or developing tools to help people reason under uncertainty. Our projects are practical in focus but intellectually demanding, drawing on ideas from simulation, human‑AI interaction, multi‑agent learning and model‑based reasoning. We are a small team with a strong research culture and a shared interest in solving meaningful and challenging problems. Everyone contributes directly to project work, and we collaborate across disciplines, whether your background is in reinforcement learning, software engineering, probabilistic modelling or systems design. We often work in partnership with researchers, government teams and other specialists, so communication and openness are important in everything we do. As a team, we value clarity over hierarchy and experimentation over perfection. We are growing steadily and carefully, with a mix of longer‑term research and near‑term applications. For someone who wants breadth, ownership and exposure to challenging applied research, this offers the chance to work across technical boundaries and influence how we grow. This may include: • Developing and implementing complex simulation environments to support machine learning model training., • Collaborating with clients and stakeholders to understand requirements and design simulation scenarios aligned with real‑world applications., • Applying expertise in modelling to create realistic and scalable simulations., • Carrying out data science activities, including data exploration and analysis, to inform simulation design and model training strategies., • Designing and implementing machine learning models, with a focus on both supervised and unsupervised learning techniques., • Exploring and implementing reinforcement learning algorithms, with a preference for experience in multi‑agent environments., • Developing and integrating physics or engineering models into simulation environments to enhance realism and accuracy., • Applying your strong software skills, including proficiency in Python and ideally another programming language., • Applying DevOps processes to ensure seamless integration of ML training pipeline., • Taking ownership of defined technical workstreams, breaking down ambiguous problems into practical next steps, and helping the team identify risks, blockers and opportunities. Someone with many of the following: • Master’s degree in Computer Science, Machine Learning or any related field., • Proven experience in programming with Python and familiarity with at least one additional programming language., • Demonstrated experience in simulation and machine learning., • Familiarity with or experience in agile project management methodologies., • Strong understanding of data science principles, including data exploration and analysis., • Proficiency in developing and implementing machine learning models, both supervised and unsupervised., • Familiarity with model development, such as physics or engineering models, for integration into simulations., • Good software development and debugging skills., • Experience with DevOps practices for efficient integration and deployment., • Optional: Experience in reinforcement learning, especially in multi‑agent environments., • Evidence of taking ownership of technical tasks or workstreams, proposing sensible next steps, and communicating risks, trade‑offs and progress without needing close supervision., • Comfortable working in a small team where engineers are expected to show initiative, lead on tasks when appropriate, and contribute ideas to project direction rather than waiting for fully specified instructions. The Aeris team comes from different personal, professional and organisational backgrounds. We are driven by a deep intellectual curiosity that powers us forward each day. You’ll learn something new from people you meet and also have the opportunity to make your mark on a growing start‑up. • Flexible working: We believe people have different responsibilities and interest that require something different to a strict working day. We trust our people to organize for their own work., • Remote working but with the opportunity to work together weekly (if in London)., • Generous pension: 8% employer salary contribution if employee pays at least 5% contribution; 5% employer contribution otherwise., • Optional private health insurance, • Eye tests and contribution towards cost of corrective lenses., • Life insurance, critical illness protection (optional) and income protection., • Social events: We have frequent socials and informal get‑togethers to help make sure you enjoy your time with us., • Professional memberships (with qualifying body). If you are passionate about pushing the boundaries of machine learning research and have the skills to contribute to our innovative projects, we invite you to apply and join our forward‑thinking team. #J-18808-Ljbffr

Salary: £50,000 - 84,000 per year • 1+ years of applied end-to-end industry experience, including internships working with complex datasets, including curation, querying, aggregation, exploratory data analysis, and visualization, • Experience using statistical methods to analyze data, identify patterns, conduct root cause analysis, discover insights, and recommend solutions, • Ability to frame and answer questions mathematically, • Ability to infer useful forward-looking directions from results of retrospective analysis, • Fluency in managing, processing, and visualizing tabular data using a combination of SQL, polars, and R, • Basic software development skills and experience with bash, linux/unix, and git, • Ability to refine requirements from ambiguous requests, • Excellence in communication and ability to produce complete and clear reports, • Bachelors degree in a quantitative discipline (statistics, biostatistics, data science, computer science, or a related field), • Masters degree in a quantitative discipline is preferred, • Prior industry experience or displayed interest in finance, such as related academic projects, coursework in financial engineering, or industry internships is preferred, • Experience developing in a production-facing environment and familiarity with standard concepts and tooling, e.g., CI/CD, Airflow is preferred, • Find insights from a complex array of data, • Conduct data curation, analysis, interpretation, visualization, and communication of findings to members of the research staff and leadership, • Design and implement systems to ensure data correctness and monitor data health in data stores and live feeds, • Proactively identify abnormal production behavior and communicate it clearly to relevant stakeholders, • Perform extemporaneous analyses on research and production trading systems with leadership, • Perform statistical analyses on production trading data and research data to inform further projects, • Design and implement analysis pipelines that automate valuable analyses for ongoing monitoring, • AI, • Airflow, • Bash, • CI/CD, • Git, • Linux, • Machine Learning, • SQL, • Unix Voleon is a technology company applying state-of-the-art AI and machine learning techniques to real-world problems in finance. For nearly two decades, we have led our industry and worked at the frontier of applying AI/ML to investment management, and we have become a multibillion-dollar asset manager with ambitious goals for the future. Our colleagues include internationally recognized experts in artificial intelligence and machine learning research as well as highly experienced finance and technology professionals. We offer a collegial working environment, highly competitive compensation and benefits packages, technology talks by our experts, a beautiful modern office, daily catered lunches, and more. This role is based in London, is full time, and is hybrid, within our Research department. last updated 40 week of 2026 #J-18808-Ljbffr

Accenture is a leading global professional services company, providing a broad range of services in strategy and consulting, interactive, technology and operations, with digital capabilities across all of these services. With our thought leadership and culture of innovation, we apply industry expertise, diverse skill sets and next-generation technology to each business challenge. We believe in inclusion and diversity and supporting the whole person. Our core values comprise of Stewardship, Best People, Client Value Creation, One Global Network, Respect for the Individual and Integrity. Year after year, Accenture is recognized worldwide not just for business performance but for inclusion and diversity too. “Across the globe, one thing is universally true of the people of Accenture: We care deeply about what we do and the impact we have with our clients and with the communities in which we work and live. It is personal to all of us.” – Julie Sweet, Accenture CEO The Data and AI revolution is changing everything. It’s everywhere – transforming how we work and play. Join Accenture and help transform leading organisations and communities around the world. Accenture Data and AI Science is driving these exciting changes and bringing them to life across 40 industries in more than 120 countries. The sheer scale of our capabilities and client engagements and the way we collaborate with the ecosystem, operate and deliver value provides an unparalleled opportunity to grow and advance. Accenture’s Data and AI practice covers the range of Data and AI skills, from Strategy, Data Science, Data Architecture, AI Engineering and Visual Insights. When combined with Accenture’s broader Strategy and Consulting practice, we are able to bring together the unique ability to drive end to end business change through the application of Data and AI. You’ll learn, grow and advance in an innovative culture that thrives on shared success, diverse ways of thinking and enables boundaryless opportunities that can drive your career in new and exciting ways. If you’re looking for a challenging career working in a vibrant environment with access to training and a global network of experts, this could be the role for you. As part of our global team, you’ll be working with cutting-edge technologies and will have the opportunity to develop a wide range of new skills on the job. • Be at the forefront of the industry, you’ll create, own and make it a reality for clients looking to better serve their connected customers and operate always-on enterprises., • Become an integral part of our Applied Intelligence team with the credibility, expertise and insight clients depend on., • Be working with famous brands and household names – no worrying about how to explain what you do to your family again!, • Develop your skills with our world class training programmes., • Drive and implement real world solutions into production that drive business value to our clients., • Work alongside global teams to collaborate and deliver the best solutions for our clients., • Drive your career progression via our structured career development programs., • Align with our industry partners to develop your career and the solutions we deliver for our clients., • Solve challenging business problems using advanced machine learning methods such as Deep Learning and quantitative analytics., • Understand business requirements and support the development of business cases., • Run discovery analytics to identify new and innovative opportunities., • Partner with developers and engineers to deploy machine learning algorithms to deliver business value., • Define approaches to embed and scale machine learning models., • Build reusable assets, solutions and develop best practices for current and future business problems., • Consult on complex analyses and advanced machine learning methods., • Communicate and provide guidance to senior client leadership and teams., • Contribute data science expertise to new sales activities., • Shape DS Strategy and the delivery of DS solutions., • Operate across multiple industries and functions., • Develop others by bringing your unique knowledge and skillsets to the wider practice., • Relevant work experience in data science, machine learning, and business analytics, • Practical experience in coding languages eg. Python, R, Scala, etc.; (Python preferred), • Proficiency in database technologies eg. SQL, ETL, No-SQL, DW, and Big Data technologies e.g. pySpark, Hive, etc., • Experienced working with structured and also unstructured data eg. Text, PDFs, jpgs, call recordings, video, etc., • Knowledge of machine learning modelling techniques and how to fine-tune those models eg. XGBoost, Deep Neural Networks, Transformers, Markov chains, etc., • Experience using specialized machine learning libraries e.g. Fastai, Keras, Tensorflow, pytorch, sci-kit learn, huggingface, etc., • Must demonstrate the capacity of reading, understanding and implementing new techniques in the field of machine learning as they emerge., • Experience of using Cloud technologies eg. AWS, GCP or Azure., • Specialised visualisation techniques eg. D3.js, ggplot etc., • Strong verbal/written communication & data presentation skills, • Awareness of Large Language Models (LLMs) and a strong enthusiasm for continuous learning and staying updated with the latest advancements in the field, • Willingness and ability to learn quickly and apply creative thinking to finding great solutions and drive their implementation, • Ability to successfully build relationships with clients and stakeholders, • Mastery of problem solving and solutioning, • Proven history and background in statistics/mathematics/macroeconomics At Accenture in addition to a competitive basic salary, you will also have an extensive benefits package which includes 30 days’ vacation per year, gym subsidy, private medical insurance and 3 extra days leave per year for charitable work of your choice! ACNDataAI ACNConsultX #J-18808-Ljbffr

Assume a critical role in defining the future of a globally recognized firm and have a direct and significant effect in a realm tailored for top achievers in site reliability. As a Lead Site Reliability Engineer at JPMorgan Chase within the Commercial and Investment Banking, Markets Technology - Athena Core team, you hold a leadership role in your team, demonstrate strong knowledge across multiple technical domains, and advise others on the technical and business issues facing them. Take lead and conduct resiliency design reviews, break up complex problems into digestible work for other engineers, act as a technical lead for medium to large-sized products, and provide advice and mentoring to other engineers. • Consistently models and champions site reliability culture and practices, documents and shares knowledge within your organization via internal forums and communities of practice, • Leads initiatives to improve the reliability and stability of your team’s applications and platforms using data-driven analytics to improve service levels, proactively identifying and solving technology-related bottlenecks in areas of expertise, • Drives collaboration with your team to identify comprehensive service level indicators and the stakeholder partners to establish reasonable service level objectives and error budgets with your customers, • Uses enterprise-authorized AI capabilities within the work environment to accelerate major-incident triage, troubleshooting, and post-incident analysis, validating outputs and handling operational data according to sensitivity and security requirements., • Serves as the main point of contact during major incidents for your application and has the skills to identify and solve the issue quickly to avoid financial loss to the business, • Offers a high level of technical expertise within one or more technical domains and provides advice and mentorship to other engineers, • Leads reuse-first adoption of AI-assisted reliability workflows across SDLC/toolchain practices (e.g., CI/CD quality checks, test/validation automation, and operational readiness), ensuring traceability/auditability, resiliency, and security controls., • Be part of the first line of support for the wider Athena Core team., • Formal training or certification on site reliability engineering concepts and applied experience, • Bachelor's Degree in Computer Science or equivalent, • Demonstrated proficiency in reliability, scalability, performance, security, enterprise system architecture, toil reduction, and other site reliability best practices, • An understanding of programming languages such as: Python, Java/Spring Boot, .Net, • Demonstrated experience using enterprise-authorized AI capabilities within the work environment to improve SRE workflows (e.g., incident investigation support and knowledge capture) with strong validation habits and awareness of data sensitivity., • Ability to evaluate AI-assisted operational recommendations for correctness and risk, define appropriate guardrails for team usage, and ensure outcomes align to resiliency and security expectations., • A strong understanding of Linux, Proficient knowledge and experience in observability such as white and black box monitoring, service level objective alerting, and telemetry collection, • Proficient with continuous integration and continuous delivery practices and tooling, • Proficient with container and container orchestration, • Experience with troubleshooting common networking technologies and issues, • Advanced knowledge of software applications and technical processes with emerging depth in one or more technical disciplines, and actively self-educates to evaluate and recommend suitable new technologies J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world’s most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation. J.P. Morgan's Commercial & Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world. Lead and conduct resiliency design reviews, break up complex problems, and act as a technical lead for medium to large sized products #J-18808-Ljbffr

OctaiPipe is on a mission to revolutionise the optimisation of energy in data centres through decentralised artificial intelligence (AI). To do this, OctaiPipe is harnessing an elegant but revolutionary idea. Rather than move the data from the source, move the algorithms to the data to learn at the data source. This learning can be achieved with the intelligence of many devices through novel federated AI technology. OctaiPipe is developing the AI for Cooling Efficiency (ACE) application to be deployed using its own in-house distributed AI platform. We are looking for a Frontend Software Engineer to join the ACE team and help build the user-facing applications at the heart of our flagship AI for Cooling Efficiency product. You will design and develop the interfaces through which customers and internal teams interact with ACE, turning complex operational, sensor and AI-generated data into intuitive, reliable and actionable experiences. Working primarily with React and TypeScript, you will take ownership of frontend features from design and architecture through to implementation, testing and deployment. You will work closely with Product, Design, Software Engineering and Applied Science to translate technically complex requirements into high-quality product experiences that can operate reliably in real-world data centre environments. • Design, build and maintain production-grade frontend applications using React, TypeScript and Next., • Build intuitive interfaces that make complex operational, time-series and AI-generated data easy for users to understand and act upon., • Develop dashboards, data visualisations, workflows and monitoring experiences, to operate and understand ACE across customer sites., • Work with large datasets, representing the data on graphs/floor plans. Apply relevant caching., • Collaborate closely with Product, Design, Applied Science and backend engineers to turn product requirements and technical concepts into robust frontend solutions., • Own features end-to-end, from technical design and estimation through implementation, testing, deployment and ongoing improvement., • Integrate frontend applications with REST APIs and backend services, handling asynchronous data, authentication, permissions and application state effectively., • Build reusable components and contribute to a scalable, consistent frontend architecture and design system., • Write clean, well-tested and maintainable code, with a strong focus on performance, reliability and usability., • Contribute to code reviews, technical discussions and decisions around frontend architecture and engineering standards., • Help diagnose and resolve product and customer issues, including those arising from real-world deployment environments., • Diagnose and solve performance issues within the application., • Strong commercial experience developing production applications with React and TypeScript, preferably with Next.js., • Excellent knowledge of modern JavaScript/TypeScript, HTML and CSS., • Strong understanding of React fundamentals, component architecture, hooks, state management and modern frontend application patterns., • Experience designing and building reusable, maintainable component systems., • Experience integrating frontend applications with REST APIs and other backend services., • Strong understanding of asynchronous application behaviour, data fetching, caching and state management., • Experience building responsive, accessible and performant web applications., • A strong approach to frontend testing, including unit, integration and end-to-end testing., • Experience with modern frontend build, package management and development tooling., • Strong Git/GitHub version control practices. #J-18808-Ljbffr

At Kyndryl, we run and reimagine the mission-critical technology systems that drive advantage for the world’s leading businesses. We are at the heart of progress; with proven expertise and a continuous flow of AI-powered insight, enabling smarter decisions, faster innovation, and a lasting competitive edge. For our people—Kyndryls that means doing purposeful work that powers human progress. Join us and experience a flexible, supportive environment where your well-being is prioritized and your potential can thrive. At Kyndryl, we run and reimagine the mission-critical technology systems that drive advantage for the world’s leading businesses. We are at the heart of progress; with proven expertise and a continuous flow of AI-powered insight, enabling smarter decisions, faster innovation, and a lasting competitive edge. For our people—Kyndryls that means doing purposeful work that powers human progress. Join us and experience a flexible, supportive environment where your well-being is prioritized and your potential can thrive. As a Forward Deployed Lead / Principal Engineer (FDE) with an AI & Agentic Engineering focus (Band 9), you own the technical direction and delivery of major enterprise AI programmes — architecting the agentic systems and generative AI applications that go into production in close collaboration with platform engineering. You align enterprise goals with target-state AI architectures for senior stakeholders, guide the team’s technical direction while staying close to the work, and work hand-in-hand with the platform engineers on the team throughout design, build, and deployment. You combine deep expertise in agentic AI systems, RAG, and applied software engineering with strong consulting acumen. You establish AI governance frameworks, champion sound engineering practice across the AI delivery lifecycle, and act as a go-to technical reference on complex engagements. Depending on the engagement, you’ll draw on some of the below more than others — not every bullet applies to every project. • Design and build agentic AI applications and multi-agent workflows, along with the frameworks that run them, for enterprise use cases, • Build RAG pipelines and integrate LLM APIs, vector databases, and MCP (Model Context Protocol) tooling, • Process unstructured data into condensed, structured knowledge, including ontology extraction, • Write production-grade Python services (FastAPI) with solid engineering practices: design, testing, code review, CI/CD, • Work with relational and graph databases (e.g.Postgres, Neo4j) to model and serve data behind AI applications, • Work closely with platform engineering throughout deployment — hosting, scaling, and MLOps/LLMOps — without owning that infrastructure yourself, • Define AI governance and responsible-use guardrails: data privacy boundaries, LLM governance, and policy enforcement (OPA/Rego), • Instrument AI applications for observability (OpenTelemetry, Prometheus) so behaviour and cost stay visible in production, • Translate enterprise requirements into AI solution roadmaps for senior stakeholders, • Capture field learnings, codify reusable agentic patterns, and mentor engineers hands-on, • Provide architectural oversight across multi-disciplinary workstreams, staying close enough to unblock the team directly You don’t need to tick every box below to apply — this reflects the breadth of the role, not a strict checklist. • 8–10+ years in software or solution engineering, with a track record of shipping AI systems in client-facing engagements, • Strong Python engineering (FastAPI), with solid SDLC practices: design, testing, code review, CI/CD, Git & GitHub, • Hands-on experience with agentic AI frameworks (examples include LangGraph, CrewAI, AutoGen, Semantic Kernel, OpenAI’s Agents SDK, and Google’s Agent Development Kit) and MCP (Model Context Protocol), • Practical experience building RAG/LLM-based pipelines and working with vector databases, • Experience with relational and graph databases (e.g.Postgres, Neo4j) for data modelling behind AI applications, • Hands-on familiarity with modern AI coding copilots (e.g.Claude, Codex, Cursor), • Strong stakeholder communication, translating AI capability into business outcomes for senior stakeholders, • Familiarity with observability instrumentation for AI systems (OpenTelemetry, Prometheus), • Experience with AI/ML frameworks (TensorFlow, PyTorch) and the Hugging Face / open-source AI ecosystem, • Experience with image understanding and OCR, • Working knowledge of policy-as-code (OPA/Rego) for AI governance and guardrails, • Understanding of LLM governance: data privacy, guardrails, and responsible-use controls, • T-shaped profile: deep expertise in AI engineering, broad understanding across software engineering and technical consulting, • Willingness to travel and work on customer premises as required, • Degree in Computer Science, Data Science, Informatics, Engineering, Physics, Mathematics, or a related discipline — or equivalent professional experience The “Kyn” in Kyndryl means kinship, which represents the strong bonds we have with each other, our customers and our communities. We focus on ensuring all Kyndryls feel included and we welcome people of all cultures, backgrounds, and experiences. Even if you don’t meet every requirement, we encourage you to apply. We believe in growth, and we’re excited to see what you can bring. At Kyndryl, employee feedback has told us that our number one driver of employee engagement is belonging. That sense of belonging — being a valued, respected, trusted member of the team — is fundamental to our culture and fueling great experiences for our customers. That’s The Kyndryl Way. Your career with us isn’t just a job—it’s an adventure with purpose. We offer a dynamic, hybrid-friendly culture that supports your well-being and empowers you to grow. Our Be Well programs are thoughtfully designed to support your financial, mental, physical, and social health—because we know that when you feel your best, you do your best. From your very first day, you’ll dive into impactful work that powers the systems our customers rely on every day. You won’t just contribute—you’ll make a difference, tackling meaningful projects that sharpen your skills and fuel your growth. We’re here to champion your journey. With powerful tools to chart your career path, personalized development goals aligned with your ambitions, and continuous feedback to keep you inspired and on track, you’ll have everything you need to thrive and evolve. You’ll develop in-demand skills to grow your career and achieve your ambitions with access to cutting-edge learning opportunities—from certifications with Microsoft, Google, and Amazon to coaching and hands-on experiences. And through it all, you’ll be part of a culture that values empathy, restless learning, and a devotion to shared success. We want you to thrive here—and we’re committed to helping you do just that. Ready to make an impact? Join us and help shape what’s next. #J-18808-Ljbffr

Job Title: Reserving Actuary Reporting to: Deputy Head of International Reserving Direct Reports: None Position Type: Permanent Hybrid Working arrangements: Working in the office Monday, Wednesday & Thursday Job Purpose: Reporting into the Deputy Head of International Reserving to support the UK actuarial function in all aspects of the reserving process including the evaluation of Solvency II technical provisions across the International Group. Key role requirements: 1. Supporting quarterly reviews of reserves in respect of P&C business written across TM HCC’s International Group platforms, including Financial Lines, Energy, Marine, Property, Renewables, Treaty, Accident & Health, Credit, Surety, Professional Indemnity and Liability lines., 2. Delivery of Solvency II technical provisions and related regulatory/Lloyd’s returns., 3. Leading ad-hoc deep-dive portfolio analyses and other relevant projects and feeding back insights to the wider business., 4. Identifying and leading technical and wider process enhancements to increase the efficiency and impact of existing processes., 5. Supporting periodic analysis of reserve risk to quantify and communicate the range of uncertainty around the actuarial best estimate and support the parameterization of key inputs to the internal capital model., 6. Liaising with other stakeholders across the company in a collaborative effort to improve processes and enhance the reputation of the actuarial team. Full details of each requirement are outlined below. Additional role expectations: • Coordinate and review analysts’ work, providing timely performance feedback and training to ensure high professional standards are met at all times., • Contribute to the growth of intellectual capital within the actuarial department through attendance and participation in professional development initiatives and events as well as sharing of specialized expertise with other members of the team., • Demonstrate accountability and forward-looking approach in execution of work, so that processes are intuitive, dynamic and scalable, with appropriate audit trails. Skills and Experience Specification: Education: • Bachelor’s degree in Actuarial Science, Mathematics, Statistics or related field., • Fellow of the Institute and Faculty of Actuaries (FIA), Fellow of the Casualty Actuarial Society (FCAS) or similar. Essential: • A minimum of 3 years core reserving experience involving practical application of actuarial methods and statistical techniques used in reserving of London Market P&C lines., • Excellent written and verbal communications skills., • Commercial awareness and knowledge of industry changes, legal updates and technical developments related to applicable areas of TM HCC’s business to proactively respond to changing business environment., • Thorough knowledge of the regulatory environment, including specific responsibilities placed on the actuarial function as part of the Solvency II framework and Lloyd’s guidance for the setting of syndicate reserves., • Strong analytical skills with aptitude for detail and ability to apply advanced problem-solving skills., • Advanced proficiency and experience using Microsoft Office Package (Excel, Access, PowerPoint, Word)., • Programming aptitude / experience e.g. VBA, SQL, Python, R or similar. Desirable: • Proficiency and experience working with ResQ, Psicle and Power BI. Requirements: additional information. Supporting quarterly reviews of reserves. Work covers: • Appropriate application of actuarial loss reserving techniques and expert judgement., • Timely delivery and communication of results to management, relevant committees and heads of underwriting business units., • Involvement in drafting formal TAS compliant reports produced by the UK actuarial function., • Coordinate and review analysts’ work, providing timely performance feedback and training to ensure high professional standards are met at all times., • Liaise with finance, claims management and business intelligence as necessary., • Co-ordinate with actuarial teams based in the United States to ensure International actuarial input is relevant and timely., • Identification and implementation of technical and other process enhancements to increase the efficiency of the reserve review process and controls around data quality., • Ongoing development and enhancement of actuarial methods and diagnostic tools applied in reserving analyses and monitoring of claims watchlist items and loss trends., • Maintenance and further development of detailed documentation of reserving assumptions and methodology as well as actuarial procedure documents., • Support with ad hoc requests from management, regulators and auditors as required, including liaising with the external actuaries to ensure timely provision of the annual Statement of Actuarial Opinion for TM HCC Syndicate 4141. Delivery of Solvency II technical provisions and related regulatory/Lloyd’s returns, including: • Update and development of key processes, model variables and assumptions used to assess Solvency II technical provisions., • Timely delivery and communication of Solvency II technical provision output to management., • Assist other business units regarding regulatory matters related to Solvency II technical provisions as required, including help with completing regulatory submissions and resolving queries from the regulator. Leading ad-hoc deep-dive portfolio analyses and other relevant projects including: • Lead meetings with underwriters and claims teams to inform the scope of deep-dive analyses., • Undertake and/or support analysts in performing analytics to further understanding of the portfolio and current trends., • Carry out research on market developments., • Prepare reports and memos summarising findings from the deep-dive analyses., • Identify and support in the implementation of enhancements in actuarial datasets, analysis and dashboards to enrich the BAU process., • Feedback findings to key stakeholders. Identifying and leading technical and wider process enhancements including: • Keep abreast of the latest market reserving practices., • Proactively identify areas for development within the reserving and technical provisions processes., • Participate in team workshops to develop proposals for development., • Undertake or manage analysts in designing and implementing process and MI improvements. Periodic analysis of reserve risk including: • Specifying and calibrating a set of statistical distributions used to model reserve risk as part of the capital setting process., • Contribute to internal model validation by implementing improvements to address prior validation findings and assisting with validation queries. Liaising with other stakeholders across the company. Work covers: • Forming relationships with key stakeholders across the Tokio Marine Group; including leadership within the relevant underwriting and claims teams., • Contributing to the sharing of intellectual capital across the organisation on emerging practices and technological developments., • Identifying opportunities to collaborate with other functions and support in workshops to develop proposals for development., • Leading and/or supporting analysts in completing collaborative projects. "Tokio Marine HCC is a leading specialty insurance group with offices in the United States, the United Kingdom, Europe, and other locations. With the strength and stability that comes from being a member of the Tokio Marine group, and more than forty years of growth, profitability, and stability, we offer important insurance products that most people do not even know exist. The Tokio Marine HCC Group of companies is an equal opportunity employer. Please visit www.tmhcc.com for more information about our companies. #LI-NW1 #J-18808-Ljbffr

Join adynamic, global analytics teamwithin JPMorgan Chase's Commercial & Investment Bank, Electronic Trading Technology. As a Lead Software Engineer at JPMorgan Chase within Commercial & Investment Bank, Electronic Trading Technology, you will play a pivotal role in designing and delivering high-performance, scalable solutions that power real-time trading and research in a fast-paced financial environment. We seek candidates with strong expertise inany of Python/KDB/C++, and who can leverage their knowledge ofAIto drive innovation in data engineering, analytics, and automation. Experience leveraging AI in development, analytics, or SDLC use cases is a critical enabler for this role. • Lead technical initiativesacross global analytics teams, providing guidance and direction to engineers, contractors, and vendors in a high-velocity environment., • Design, build, and optimize real-time data processing pipelines and applications ensuring reliability and performance for mission-critical financial systems., • Leverage AI technologies and techniquesto enhance data engineering workflows, automate SDLC processes, and deliver advanced analytics capabilities for trading and research., • Collaborate with research and trading teams worldwideto onboard new datasets efficiently and consistently, supporting global business needs., • Build and support robust tools and frameworksfor quantitative research and production trading, including scalable APIs and analytics libraries., • Mentor and develop team members, manage book of work, and drive continuous improvement in SDLC, testing, and coding standards across distributed teams., • Influence product design, application functionality, and technical operations/processesto meet the demands of a rapidly evolving financial landscape., • Serve as a subject matter expertin Python, KDB/Q, data engineering, and AI, contributing to firmwide best practices and technical excellence., • Champion diversity, inclusion, and collaborationwithin large, global teams., • 5+ years of applied experience in software engineering, in large-scale, fast-paced financial environments., • Hands-on experience delivering system design, application development, testing, and operational stability for analytics-driven teams., • Strong expertise in any of Python/KDB/C++, for real-time data processing, application development, or data engineering., • Working knowledge of AI technologies(machine learning, generative AI, etc.) to support data engineering, analytics, or SDLC automation., • Proficiency in automation and continuous delivery methods; advanced understanding of agile methodologies (CI/CD, Application Resiliency, Security)., • Experience leading and mentoring teams in a global, collaborative environment., • Ability to tackle complex design and functionality problems independently and drive solutions across distributed teams., • Academic background in Computer Science, Computer Engineering, Mathematics, or a related technical field., • Experience with market data venue and vendor data platforms., • AWS experience; practical cloud native/cloud experience is a plus., • Experience with Terraform and Kubernetes for managing production environments in public cloud., • Strong knowledge and experience in FIX, Market Data, Analytics, OMS, and equities trading in global markets are assets., • Knowledge of machine learning, statistical techniques, and related libraries. #J-18808-Ljbffr

Voleon is a technology company that applies state-of-the-art AI and machine learning techniques to real-world problems in finance. For nearly two decades, we have led our industry and worked at the frontier of applying AI/ML to investment management. We have become a multibillion-dollar asset manager, and we have ambitious goals for the future. Your colleagues will include internationally recognized experts in artificial intelligence and machine learning research as well as highly experienced finance and technology professionals. In addition to our enriching and collegial working environment, we offer highly competitive compensation and benefits packages, technology talks by our experts, a beautiful modern office, daily catered lunches, and more. As a Senior Machine Learning Engineer on one of Voleon's Research teams, you will partner directly with research staff to advance our quantitative trading strategies. You will translate novel research ideas into production-quality code, build and maintain the data pipelines and modeling infrastructure that underpin our strategies, and apply your own strong mathematical intuition to solve open-ended technical challenges. This role lives at the boundary of research and engineering. You will be expected to understand the statistical and mathematical concepts your research partners work with, contribute meaningfully to technical discussions about model design and evaluation, and ensure that the resulting systems are performant, reliable, and maintainable. You will work at the intersection of Computer Science, Mathematics, and Statistics - building high-performance tools that enable world-class research while maintaining a high engineering standard. Partner with PhD researchers to design, implement, and productize machine learning models that drive quantitative trading strategies Develop and maintain complex data pipelines, including data ingestion, feature engineering, validation, and quality monitoring Translate research prototypes and novel ideas into performant, well-tested, production-ready code Build extensible tools and frameworks that accelerate the model development and experimentation lifecycle Supervise, understand, and remediate subtle data quality issues across both research and production environments Proactively lead projects from requirements through delivery, making autonomous decisions about scope, dependencies, and trade-offs, with an emphasis on long-term maintainability Coordinate and contribute to deployment efforts while guiding junior engineers and researchers; align with research and engineering stakeholders on ownership, execution, and prioritization Foster engineering consistency, standards, and best practices within Research Bachelor's degree (or higher) in Computer Science, Applied Mathematics, Statistics, or a related quantitative field 5+ years of professional software engineering experience, with strong CS fundamentals (data structures, algorithms, systems design) Demonstrated mathematical maturity - comfort with the concepts and notation used in statistics, linear algebra, optimization, and probability Deep proficiency in Python; experience with R and/or C/C++ is a strong plus Extensive experience with numerical and data science libraries (e.g., NumPy, Pandas, SciPy, scikit-learn, PyTorch, TensorFlow, or similar) Proven experience building or maintaining machine learning systems in a distributed computing environment Proficiency developing in a Linux environment with attention to performance, correctness, and reproducibility Exceptional attention to detail, particularly when working with imperfect or heterogeneous data Strong verbal and written communication skills, and the ability to collaborate effectively with researchers whose primary expertise is not software engineering Experience with experiment management, model evaluation pipelines, or ML workflow orchestration Familiarity with modern ML/AI infrastructure patterns (model serving, feature stores, distributed training) Experience with performance profiling and optimization of numerical or modeling code Prior exposure to financial data, time-series analysis, or quantitative research environments If you have a great candidate in mind for this role and would like to have the potential to earn $15,000 if your referred candidate is successfully hired and employed by The Voleon Group, please use this form to submit your referral. For more details regarding eligibility, terms and conditions please make sure to review the Voleon Referral Bonus Program. The Voleon Group is an Equal Opportunity employer. Applicants are considered without regard to race, color, religion, creed, national origin, age, sex, gender, marital status, sexual orientation and identity, genetic information, veteran status, citizenship, or any other factors prohibited by local, state, or federal law. #J-18808-Ljbffr

At Kyndryl, we run and reimagine the mission-critical technology systems that drive advantage for the world’s leading businesses. We are at the heart of progress; with proven expertise and a continuous flow of AI-powered insight, enabling smarter decisions, faster innovation, and a lasting competitive edge. For our people—Kyndryls—that means doing purposeful work that powers human progress. Join us and experience a flexible, supportive environment where your well-being is prioritized and your potential can thrive. Your Role As a Forward Deployed Lead / Principal Engineer (FDE) with an AI & Agentic Engineering focus (Band 9), you own the technical direction and delivery of major enterprise AI programmes - architecting the agentic systems and generative AI applications that go into production in close collaboration with platform engineering. You align enterprise goals with target-state AI architectures for senior stakeholders, guide the team’s technical direction while staying close to the work, and work hand-in-hand with the platform engineers on the team throughout design, build, and deployment. You combine deep expertise in agentic AI systems, RAG, and applied software engineering with strong consulting acumen. You establish AI governance frameworks, champion sound engineering practice across the AI delivery lifecycle, and act as a go-to technical reference on complex engagements. • Design and build agentic AI applications and multi-agent workflows, along with the frameworks that run them, for enterprise use cases, • Build RAG pipelines and integrate LLM APIs, vector databases, and MCP (Model Context Protocol) tooling, • Process unstructured data into condensed, structured knowledge, including ontology extraction, • Write production‑grade Python services (FastAPI) with solid engineering practices: design, testing, code review, CI/CD, • Work with relational and graph databases (e.g. Postgres, Neo4j) to model and serve data behind AI applications, • Work closely with platform engineering throughout deployment - hosting, scaling, and MLOps/LLMOps - without owning that infrastructure yourself, • Define AI governance and responsible-use guardrails: data privacy boundaries, LLM governance, and policy enforcement (OPA/Rego), • Instrument AI applications for observability (OpenTelemetry, Prometheus) so behaviour and cost stay visible in production, • Translate enterprise requirements into AI solution roadmaps for senior stakeholders, • Capture field learnings, codify reusable agentic patterns, and mentor engineers hands‑on, • Provide architectural oversight across multi-disciplinary workstreams, staying close enough to unblock the team directly You don’t need to tick every box below to apply — this reflects the breadth of the role, not a strict checklist. • 8–10+ years in software or solution engineering, with a track record of shipping AI systems in client‑facing engagements, • Strong Python engineering (FastAPI), with solid SDLC practices: design, testing, code review, CI/CD, Git & GitHub, • Hands‑on experience with agentic AI frameworks (examples include LangGraph, CrewAI, AutoGen, Semantic Kernel, OpenAI’s Agents SDK, and Google’s Agent Development Kit) and MCP (Model Context Protocol), • Practical experience building RAG/LLM‑based pipelines and working with vector databases, • Experience with relational and graph databases (e.g. Postgres, Neo4j) for data modelling behind AI applications, • Hands‑on familiarity with modern AI coding copilots (e.g. Claude, Codex, Cursor), • Strong stakeholder communication, translating AI capability into business outcomes for senior stakeholders, • Willingness to travel and work on customer premises as required, • Degree in Computer Science, Data Science, Informatics, Engineering, Physics, Mathematics, or a related discipline — or equivalent professional experience, • Familiarity with observability instrumentation for AI systems (OpenTelemetry, Prometheus), • Experience with AI/ML frameworks (TensorFlow, PyTorch) and the Hugging Face / open‑source AI ecosystem, • Experience with image understanding and OCR, • Working knowledge of policy‑as‑code (OPA/Rego) for AI governance and guardrails, • Understanding of LLM governance: data privacy, guardrails, and responsible‑use controls, • T‑shaped profile: deep expertise in AI engineering, broad understanding across software engineering and technical consulting We focus on ensuring all Kyndryls feel included and we welcome people of all cultures, backgrounds, and experiences. Even if you don’t meet every requirement, we encourage you to apply. We believe in growth, and we’re excited to see what you can bring. At Kyndryl, employee feedback has told us that our number one driver of employee engagement is belonging. That sense of belonging — being a valued, respected, trusted member of the team — is fundamental to our culture and fueling great experiences for our customers. That’s The Kyndryl Way. Our dynamic, hybrid‑friendly culture supports your well‑being and empowers you to grow. Our Be Well programs are thoughtfully designed to support your financial, mental, physical, and social health—because we know that when you feel your best, you do your best. From your very first day, you’ll dive into impactful work that powers the systems our customers rely on every day. You won’t just contribute—you’ll make a difference, tackling meaningful projects that sharpen your skills and fuel your growth. We’ll champion your journey. With powerful tools to chart your career path, personalized development goals aligned with your ambitions, and continuous feedback to keep you inspired and on track, you’ll have everything you need to thrive and evolve. You’ll develop in‑demand skills to grow your career and achieve your ambitions with access to cutting‑edge learning opportunities—from certifications with Microsoft, Google, and Amazon to coaching and hands‑on experiences. And through it all, you’ll be part of a culture that values empathy, restless learning, and a devotion to shared success. We want you to thrive here—and we’re committed to helping you do just that. At Kyndryl, we achieve progress the world depends on, with purpose. Beginning with the purpose that matters to you. Because here, you will be part of a culture designed with purpose. One that is restless, empathetic and devoted. Where we are committed to sustainable progress for our customers and supporting the communities where we work and live. All of you is what we want. And what we need. Join us, and together, we can advance the vital systems that power human progress. #J-18808-Ljbffr

Voleon is a technology company that applies state-of-the-art AI and machine learning techniques to real-world problems in finance. For nearly two decades, we have led our industry and worked at the frontier of applying AI/ML to investment management. We have become a multibillion-dollar asset manager, and we have ambitious goals for the future. Your colleagues will include internationally recognized experts in artificial intelligence and machine learning research as well as highly experienced finance and technology professionals. In addition to our enriching and collegial working environment, we offer highly competitive compensation and benefits packages, technology talks by our experts, a beautiful modern office, daily catered lunches, and more. As a Senior Machine Learning Engineer on one of Voleon's Research teams, you will partner directly with research staff to advance our quantitative trading strategies. You will translate novel research ideas into production-quality code, build and maintain the data pipelines and modeling infrastructure that underpin our strategies, and apply your own strong mathematical intuition to solve open-ended technical challenges. This role lives at the boundary of research and engineering. You will be expected to understand the statistical and mathematical concepts your research partners work with, contribute meaningfully to technical discussions about model design and evaluation, and ensure that the resulting systems are performant, reliable, and maintainable. You will work at the intersection of Computer Science, Mathematics, and Statistics - building high-performance tools that enable world-class research while maintaining a high engineering standard. • Partner with PhD researchers to design, implement, and productize machine learning models that drive quantitative trading strategies, • Develop and maintain complex data pipelines, including data ingestion, feature engineering, validation, and quality monitoring, • Translate research prototypes and novel ideas into performant, well-tested, production-ready code, • Build extensible tools and frameworks that accelerate the model development and experimentation lifecycle, • Supervise, understand, and remediate subtle data quality issues across both research and production environments, • Proactively lead projects from requirements through delivery, making autonomous decisions about scope, dependencies, and trade-offs, with an emphasis on long-term maintainability, • Coordinate and contribute to deployment efforts while guiding junior engineers and researchers; align with research and engineering stakeholders on ownership, execution, and prioritization, • Foster engineering consistency, standards, and best practices within Research, • Bachelor's degree (or higher) in Computer Science, Applied Mathematics, Statistics, or a related quantitative field, • 5+ years of professional software engineering experience, with strong CS fundamentals (data structures, algorithms, systems design), • Demonstrated mathematical maturity - comfort with the concepts and notation used in statistics, linear algebra, optimization, and probability, • Deep proficiency in Python; experience with R and/or C/C++ is a strong plus, • Extensive experience with numerical and data science libraries (e.g., NumPy, Pandas, SciPy, scikit-learn, PyTorch, TensorFlow, or similar), • Proven experience building or maintaining machine learning systems in a distributed computing environment, • Proficiency developing in a Linux environment with attention to performance, correctness, and reproducibility, • Exceptional attention to detail, particularly when working with imperfect or heterogeneous data, • Strong verbal and written communication skills, and the ability to collaborate effectively with researchers whose primary expertise is not software engineering, • Experience with experiment management, model evaluation pipelines, or ML workflow orchestration, • Familiarity with modern ML/AI infrastructure patterns (model serving, feature stores, distributed training), • Experience with performance profiling and optimization of numerical or modeling code, • Prior exposure to financial data, time-series analysis, or quantitative research environments If you have a great candidate in mind for this role and would like to have the potential to earn $15,000 if your referred candidate is successfully hired and employed by The Voleon Group, please use this form to submit your referral. For more details regarding eligibility, terms and conditions please make sure to review the Voleon Referral Bonus Program. The Voleon Group is an Equal Opportunity employer. Applicants are considered without regard to race, color, religion, creed, national origin, age, sex, gender, marital status, sexual orientation and identity, #J-18808-Ljbffr

You will join NTT DATA UK's Data Practice, a multi-disciplinary team delivering enterprise-scale data platforms, analytics and data-led transformation for clients. As part of the growing Data Science capability within the Data Practice, you will work on Machine Learning, Predictive Analytics and Applied AI use cases that help clients move beyond traditional reporting towards evidence-led, AI-enabled decision making. You will work alongside data engineers, data architects, platform specialists and consultants across Snowflake, Databricks and Microsoft Fabric to develop practical, production-ready machine learning solutions. We are looking for a Data Scientist with a solid background in Machine Learning, Statistics and Predictive Analytics to join NTT DATA UK's Data Practice. You will contribute hands‑on across the model development lifecycle, from data understanding and feature engineering through to model training, evaluation, deployment support and ongoing improvement. Experience with Generative / Agentic AI, LLMs and AI-enabled products is preferred, but the core of this role is strong applied machine learning capability rather than AI tooling alone. • Develop machine learning models for forecasting, classification, recommendation, optimisation, clustering and anomaly detection., • Apply statistical and machine learning techniques to analyse structured and semi-structured datasets., • Perform exploratory data analysis, feature engineering, model training, validation and model evaluation., • Compare model approaches, select appropriate metrics and explain technical trade-offs clearly., • Build reusable notebooks, scripts and pipelines that support repeatable machine learning delivery., • Support monitoring and continuous improvement of models used in pilot or production environments., • Work with consultants and client stakeholders to understand business problems and translate them into analytical tasks., • Frame ambiguous questions into testable hypotheses, analytical approaches and measurable outcomes., • Communicate insights, model outputs and recommendations in a clear, practical and business-relevant way., • Support proof‑of‑concepts, project delivery, estimates, solution options and technical documentation where required., • Work with Data Engineering and Architecture teams to access, prepare and validate data for machine learning workloads., • Use platforms such as Snowflake, Databricks and Microsoft Fabric where appropriate for data preparation, experimentation and deployment support., • Follow good engineering practices for version control, testing, documentation and reproducibility., • Contribute to MLOps ways of working, including model versioning, deployment handover and performance monitoring., • Consider model explainability, data quality, bias, privacy and responsible AI implications where relevant., • 3-5 years of commercial experience in Data Science, Machine Learning or Advanced Analytics roles., • Strong hands‑on Python experience for data analysis, feature engineering and model development., • Strong SQL skills and experience working with complex or sizeable datasets., • Solid theoretical and practical understanding of supervised learning, unsupervised learning, statistical modelling, feature engineering, validation, model evaluation and optimisation., • Hands‑on experience with Python-based machine learning libraries, especially Scikit‑Learn and at least one of XGBoost, LightGBM, TensorFlow or PyTorch., • Experience developing models beyond exploratory analysis into reusable, documented and testable assets, ideally with exposure to pilot or production environments., • Strong understanding of model evaluation, including appropriate metrics, validation approaches, overfitting, data leakage, baseline comparison and business impact assessment., • Ability to explain model assumptions, limitations, drivers and risks, including awareness of model explainability, bias, data quality and responsible AI considerations., • Clear communication skills and the ability to work collaboratively in mixed technical and business teams., • Exposure to pilot or production deployment of machine learning models., • Good understanding of MLOps concepts such as versioning, reproducibility, monitoring and deployment handover., • Experience with at least one modern cloud data or analytics platform, such as Snowflake, Databricks, Microsoft Fabric, Azure, AWS or GCP., • MSc or equivalent experience in Data Science, Statistics, Mathematics, Computer Science, Artificial Intelligence, Physics, Engineering or a related quantitative discipline., • Experience with Spark or distributed data processing frameworks., • Experience preparing data pipelines or analytical datasets to support machine learning workloads., • Awareness of data engineering, data architecture, data governance and enterprise data platform concepts. NTT DATA UK&I is an ambitious business, and we want our people to be ambitious too: in your outlook, attitude and career goals. Building on our amazing heritage, we are embracing future opportunities with positivity, energy and commitment. Working together, we can create a positive, rewarding and inclusive culture. Our commitment is to provide a forward‑looking, equitable and rewarding place to work. We are developing programmes and initiatives to help our people to feel encouraged, appreciated and valued: we want you to feel like you belong here. Your commitment is to reimagine and reinvent the possible, in your day‑to‑day work and how you interact with clients. This can mean challenging accepted wisdom, asking the right questions, making more meaningful connections. We’re working to provide an environment where that’s possible, in the belief that you cannot achieve your best without feeling energised and motivated. The outcome is to create a place where you can thrive - where your growth and development are nurtured in a culture that celebrates creativity, innovation, and teamwork. We’re committed to fostering an environment that not only makes you want to stay but inspires you to reach new heights. At the heart of everything we do is our belief in the power of people, the deep, one‑to‑one relationships we build with you, and the lasting connections you create with clients. We want you to grow with us because when you succeed, we all shine. Our inclusive work environment prioritises mutual respect, accountability, andcontinuous learning for all our people. We are also proud to share that we have a range of Inclusion Networks such as: the Women’s Business Network, Cultural and Ethnicity Network, LGBTQ+ & Allies Network, Neurodiversity Network and the Parent Network. to accelerate client success and positively impact society through responsible innovation • Respect every voice. We grow by listening. We invite different viewpoints, honor every background and encourage sharing perspectives to learn from one another., • Think big. Be bold. We stretch beyond what's expected. Curiosity fuels us, ambition drives us and innovation is how we push boundaries to shape the future., • Deliver the outcome. We build trust by keeping our word. We act with integrity and hold ourselves accountable – always choosing to do the right thing., • Win together. We lift each other up. We collaborate across borders, share openly and succeed as one global team. We offer a range of tailored benefits that support your physical, emotional, and financial wellbeing. Our Learning and Development team ensure that there are continuous growth and development opportunities for our people. We also offer the opportunity to have flexible work options. We are an equal opportunities employer. We believe in the fair treatment of all our employees and commit to promoting equity and diversity in our employment practices. We are also a Disability Confident Committed Employer - we want to see every candidate performing at their best throughout the job application and interview process, if you require any reasonable adjustments during the recruitment process, please let us know and we look forward to hearing from you. #J-18808-Ljbffr

• Competitive salary and compensation structure, • Generous paid time off and holiday schedule, • Frequent firm-wide social events and activities, • Excellent environment for learning and growth, • Further benefits, depending on location, • Competitive salary and compensation structure, • Generous paid time off and holiday schedule, • Frequent firm-wide social events and activities, • Excellent environment for learning and growth, • Further benefits, depending on location We are looking for Applied AI / ML Engineers, early in their careers, who are excited by the current generation of AI-native software development. This is a hands‑on builder role: you will help design, build, test and deploy practical AI workflows and data science capabilities using Python, LLMs, AWS and Claude Code. The most important attribute is that you already use modern AI tools to build faster and better. Claude Code is our primary way of building, so we want people who are fluent and fast with it, with the judgement to know when to check and use its output and when to change it. You should be equally keen to build and operate real systems in AWS, driving that infrastructure through Claude Code itself. You may come from a data science, machine learning, software engineering or technical STEM background. Traditional data science skills such as experimentation, model evaluation, data analysis and pipeline development are useful and welcome, but they are not the current centre of gravity for this role. The core of the job is building: AI‑native tools, automated workflows, and the infrastructure that turns ideas into deployed capabilities. • Use Claude Code and other frontier AI tools to accelerate development, prototyping, debugging and documentation., • Build practical LLM workflows, agents, skills and tools that support advisory teams, client delivery and internal operations., • Implement reusable AI capabilities using OpenWebUI, LiteLLM and MCP tools., • Work across prompting, context engineering, structured outputs, evaluation, provider routing and human‑in‑the‑loop workflows., • Move useful applications and automations quickly from prototype to production., • Review and improve AI‑generated code, not just generate it: read it, test it, and make it maintainable and safe to ship., • Stand up, deploy and operate the AWS services your tools run on, working with EC2, ECS, S3, Lambda, IAM and CloudWatch., • Increasingly drive and operate AWS directly through Claude Code, infrastructure‑as‑code and agentic tooling., • Support automated deployment, monitoring, logging, cost control and observability., • Apply DevOps and MLOps practices pragmatically, working with DevOps and engineering colleagues to keep systems reliable, maintainable and easy to operate., • Use Python, SQL and APIs to build applied AI and analytics capabilities., • Help process and enrich large volumes of text and unstructured content., • Contribute to workflows involving summarisation, classification, topic identification, sentiment, contextualisation, embeddings, vector search and RAG., • Help evaluate AI outputs for quality, reliability, cost and usability, and document approaches clearly so others can understand, trust and reuse them., • Take ownership of defined tasks, prototypes and production improvements., • Take direction well and level up quickly; you will be coached hard and expected to become faster and more independent over time., • Join hackathons, experiments and rapid delivery cycles, and stay curious about new AI tools, models and agentic patterns., • Share what you learn and help raise Penta’s practical AI capability. The Data Science team sits within Penta’s Technology function, alongside Development, Engineering / DevOps & Platform Security, IT and the PMO, and works hand in hand with Product and the advisory teams. We are rebuilding and expanding the team around a practical, AI‑native roadmap. The focus is not academic research or traditional data science in isolation; it is building useful, reliable AI‑enabled tools and workflows that improve how Penta serves clients and how our internal teams work. You will work under the VP / Head of Data Science, contributing hands‑on to applied AI systems, LLM workflows, agentic tools, reusable skills, internal automation and production‑ready capabilities. The environment is collaborative, pragmatic and delivery-focused. We move quickly, share ideas openly, and value people who can turn ambiguity into working software. You will build a lot, ship often, and be coached closely as you grow. We are forward‑thinking and ambitious in practically applying AI across client‑facing work, corporate teams, technology and data science. We do not train our own foundation models; we apply, orchestrate and evaluate the best available models from major providers, engineering them into robust workflows that solve real business problems. We validate and document our methodologies through white papers and technical explainers, setting out the academic and analytical foundations behind our products, and the evidence that supports their use. This helps build trust in our tools, why they work and shows how they can be applied. We build on open‑source AI software, including LiteLLM and OpenWebUI, to maximise the internal value of AI and build durable institutional capability. Reliability, cost control, observability, instruction‑following, usability and adoption matter most. The team designs reusable workflows, skills, models and MCP tools that support Penta’s move towards an AI‑native advisory operating system. Keeping Penta at the forefront of practical AI in PR, communications and strategic consultancy is part of the role. Success means you are helping Penta ship useful AI and data science capabilities into real workflows. Within the first few months, you should be contributing to working prototypes, internal tools, AI workflows, AWS deployments and production improvements. Over time, you should become increasingly independent in building reliable, maintainable AI‑native systems that improve client delivery and internal productivity. • Empathy and collaboration, • Pushing our ideas, • Facing adversity, • Ownership and leadership We do not expect candidates at this level to have deep experience in every area. We are looking for strong potential, practical ability, and clear evidence that you already build with modern AI tools. Hands‑on experience with at least one AI‑native building tool or platform is mandatory, and we will want to see examples of what you have made with it. • Hands‑on experience building with at least one modern AI‑native tool or platform, for example Claude Code, Codex, OpenWebUI, LiteLLM or Cowork / OpenCowork (or similar), with concrete examples of what you have built with it., • Strong Python coding ability: enough to build, read, test and debug real software., • Strong prompting and context‑engineering skills, and familiarity with using LLMs in real workflows., • Comfort with APIs, JSON, structured outputs and everyday developer tooling., • Basic to intermediate SQL., • Git version control., • Strong debugging, problem‑solving and self‑learning skills., • A bias towards shipping working software, not just analysis or notebooks., • Breadth across AI‑native tools, MCP tools and agentic frameworks., • Experience building small apps, internal tools, automations or backend services, and with Docker or containerised development., • Experience with embeddings, vector databases, RAG or semantic search, and with evaluating LLM outputs for quality, accuracy, cost and reliability., • Experience processing large volumes of text or unstructured content., • Any hands‑on AWS experience (EC2, ECS, S3, Lambda, CloudWatch, IAM, infrastructure‑as‑code or CI/CD) is a plus. You will also develop this on the job, increasingly by driving AWS through Claude Code., • Foundational machine learning knowledge, and classic NLP such as classification, clustering or model selection., • Experience with hypothesis‑led data science., • A technical degree in Computer Science, Software Engineering, Data Science, Machine Learning, Maths, Physics or a related field. Welcome, but not required if the building track record is there., • A practical builder who enjoys turning ideas into working tools., • AI‑native in how they work, using AI tools as a normal part of development., • Curious, fast‑learning and comfortable with ambiguity., • Technically rigorous without being academic for its own sake., • Sound in their judgement about AI output: healthily sceptical, and in the habit of testing and verifying rather than trusting blindly., • Comfortable asking questions and learning from senior colleagues., • Able to communicate technical ideas clearly to technical and non‑technical people., • Focused on usefulness, reliability, cost and maintainability., • Excited to help build an AI‑native advisory operating system. Penta Group is a global company providing data‑driven solutions to help clients achieve their objectives in an increasingly complex stakeholder environment. We provide cutting‑edge intelligence products to help clients understand what their stakeholders think, see, and hear, and then leverage that intelligence to develop and execute effective, measurable strategies. Our global team brings decades of experience in business, government, communications, research, data science, and media. Our clients include companies across a variety of industries, including technology, financial services, energy, healthcare, and more. Penta has offices in New York, London, Washington, DC, San Francisco, Dublin, London, Brussels, Singapore, and Hong Kong. #J-18808-Ljbffr

ZS is a place where passion changes lives. As a management consulting and technology firm focused on improving life and how we live it, we transform ideas into impact by bringing together data, science, technology and human ingenuity to deliver better outcomes for all. Here you’ll work side-by-side with a powerful collective of thinkers and experts shaping life-changing solutions for patients, caregivers and consumers, worldwide. ZSers drive impact by bringing a client-first mentality to each and every engagement. We partner collaboratively with our clients to develop custom solutions and technology products that create value and deliver company results across critical areas of their business. Bring your curiosity for learning, bold ideas, courage and passion to drive life-changing impact to ZS. Decision Analytics Associates (DAAs) design and execute analyses to address business problems for our clients and project teams. DAAs leverage their analytic skills to find data-driven insights that help our clients solve their most important business problems, and engage with clients to help them understand the implications and make plans to act on them. What you'll do: • Develop and apply advanced statistical models that help clients understand dynamic business issues., • Leverage analytic techniques to use data to guide client and ZS team decision-making., • Use tools like R, Tableau, SAS, Visual Basic and Excel to investigate and inform client needs., • Synthesize and communicate results to clients and ZS teams., • Collaborate with client and ZS teams to implement solutions., • Take immediate responsibility for project deliverables. What you'll bring: • Candidates should have a Bachelors, Masters or PhD in any discipline with strong academic performance in quantitative and analytic coursework such as operations research, applied mathematics, management science, data science, statistics, econometrics or engineering., • Demonstrated proficiency in a programming language or analytic tool such as R, SAS, Tableau, or VBA., • High motivation, good work ethic, maturity and personal initiative., • Effective oral and written communication skills (fluency in English)., • Empathy, adaptability and emotional intelligence., • Strong attention to detail, with a quality-focused mindset., • Self-discipline for planning and organizing tasks., • Aptitude for, and enjoyment of, working in teams., • Fluency in English, • Client-first mentality, • Intense work ethic, • Collaborative spirit and problem-solving approach How you’ll grow: • Cross-functional skills development & custom learning pathways, • Milestone training programs aligned to career progression opportunities, • Internal mobility paths that empower growth via s-curves, individual contribution and role expansions Perks & Benefits: At ZS, your growth matters. We offer a comprehensive total rewards package that supports your health and well‑being, financial future, time away, and professional development. With robust skills‑building programs, multiple career progression paths, internal mobility, and a deeply collaborative culture, you’ll have the opportunity to do meaningful work, expand your capabilities, and thrive as part of a global community. For details on total rewards in United Kingdom, visit ZS UK office locations | Where we work | ZS. Hybrid working model: We are committed to giving our employees a flexible and connected way of working. A flexible and connected ZS allows us to combine work from home and on-site presence at clients/ZS offices for the majority of our week. The magic of ZS culture and innovation thrives in both planned and spontaneous face-to-face connections. Travel: Travel is a requirement at ZS for client facing ZSers; business needs of your project and client are the priority. While some projects may be local, all client-facing ZSers should be prepared to travel as needed. Travel provides opportunities to strengthen client relationships, gain diverse experiences, and enhance professional growth by working in different environments and cultures. Considering applying? At ZS, we honor the visible and invisible elements of our identities, personal experiences, and belief systems—the ones that comprise us as individuals, shape who we are, and make us unique. We believe your personal interests, identities, and desire to learn are integral to your success here. We are committed to building a team that reflects a broad variety of backgrounds, perspectives, and experiences. Learn moreabout our inclusion and belonging efforts and the networks ZS supports to assist our ZSers in cultivating community spaces and obtaining the resources they need to thrive. If you’re eager to grow, contribute, and bring your unique self to our work, we encourage you to apply. ZS is an equal opportunity employer and is committed to providing equal employment and advancement opportunities without regard to any class protected by applicable law. To complete your application: Candidates must possess or be able to obtain work authorization for their intended country of employment. An on-line application, including a full set of transcripts (official or unofficial), is required to be considered. NO AGENCY CALLS, PLEASE. Find Out More At: www.zs.com #J-18808-Ljbffr

N Location London Job type Not specified Posted 14 Oct 2026 (1 day ago) Region UK Source Arbeitnow Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. Nebius Token Factory is looking for scientists who can turn frontier LLM and VLM inference bottlenecks into research questions, conduct rigorous experiments, and translate their findings into production capabilities. You will own focused research and optimization projects, write strong code, and produce prototypes, publications, and technical artifacts that engineers can build on. Your research will span quantization, distillation, speculative decoding, KV-cache optimization, and model/runtime co-optimization, alongside inference engines and distributed inference architectures. You will investigate how these approaches interact, evaluate their trade-offs across model quality, latency, throughput, memory footprint, and cost per token, and work with engineering teams to bring promising results into production. • Lead research projects in efficient LLM and VLM inference, from hypotheses and experiments through ablations, prototypes, and production handoff., • Develop and evaluate methods spanning quantization, quantization-aware training (QAT), distillation, speculative decoding, KV-cache reuse, KV-cache compression, long-context inference, MoE routing, and model/runtime co-optimization., • Build prototypes using PyTorch, Triton, CUDA-adjacent tooling, or inference-serving frameworks, and collaborate with MLEs and platform engineers to turn them into production components., • Research LLM request routing and scheduling strategies, including cache-aware load balancing and prefill–decode disaggregation (PDD). Evaluate how queueing, KV-cache transfer, worker placement, and prefill/decode capacity allocation affect latency, throughput, and serving cost., • Investigate multi-node inference for dense and mixture-of-experts models, including wide expert parallelism (WideEP). Study expert placement, load imbalance, and computation/communication trade-offs, and use the findings to guide model and system architecture choices., • Develop rigorous evaluations covering quality, latency, throughput, numerical stability, memory footprint, tail latency, and cost per token. Compare serving architectures under consistent workload conditions and GPU budgets., • Work with MLE, GPU kernel, backend infrastructure, product, and customer teams to select research priorities with measurable production impact., • Share results through internal reports, technical blogs, papers, and open-source artifacts, and mentor engineers and scientists on experimental design, scientific rigor, and model/system trade-offs., • A PhD in computer science, machine learning, ML systems, computer systems, computer architecture, electrical engineering, applied mathematics, or a closely related discipline., • A strong publication record or equivalent research artifacts in ML, ML systems, efficient inference, model compression, quantization, distillation, serving systems, or related areas., • Strong Python and PyTorch implementation skills, with the ability to turn ideas into experiments and working prototypes., • Deep knowledge of LLMs, VLMs, transformer inference, decoding algorithms, model compression, quantization, and production-serving trade-offs., • Strong experimental design skills covering ablations, baselines, metrics, statistical reasoning, and failure analysis., • First-author publications at venues such as NeurIPS, ICML, ICLR, MLSys, ACL, EMNLP, ASPLOS, OSDI, SOSP, ISCA, or HPCA., • Experience deploying ML models or inference optimizations in production., • Experience with vLLM, SGLang, TensorRT-LLM, NVIDIA Dynamo, FlashAttention, FlashInfer, Triton, CUDA, or PyTorch internals., • Experience applying post-training, SFT, DPO, RLHF, RLAIF, preference optimization, or synthetic data generation to inference quality or efficiency., • Open-source research artifacts, widely used benchmarks, technical blogs, or invited talks demonstrating contributions to efficient AI systems., • Research or implementation experience in one or more areas of distributed inference system architecture, such as LLM request routing, PDD, multi-node serving, or MoE expert parallelism, including WideEP., • Competitive compensation, • Career growth and learning opportunities, • Flexibility and ownership, • Collaborative and innovative culture, • Opportunity to work on impactful AI projects, • International environment and talented teams Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know. Nebius is hiring for Senior Applied Scientist, Efficient LLM Inference & Model Optimization in London, listed via Arbeitnow. See all jobs at Nebius > Senior Applied Scientist, Efficient LLM Inference & Model Optimization · Nebius · London #J-18808-Ljbffr

We’re ASOS, the online retailer for fashion lovers all around the world. We exist to give our customers the confidence to be whoever they want to be, and that goes for our people too. At ASOS, you’re free to be your true self without judgement, and channel your creativity into a platform used by millions. But how are we showing up? We’re proud members of Inclusive Companies, are Disability Confident Committed and have signed the Business in the Community Race at Work Charter, and we placed 8th in the Inclusive Top 50 Companies Employer list. Everyone needs some help showing up as their best self. Let our Talent team know if you need any adjustments throughout the process in whatever way works best for you. Join the team responsible for building the data and machine learning products that power customer experiences, marketing effectiveness and commercial decision-making across ASOS. • Designing and building scalable data pipelines that support machine learning, analytics and data science initiatives., • Developing high-performance data solutions using Python, Spark, Databricks and Azure technologies., • Creating and maintaining datasets that power customer, marketing, pricing and forecasting use cases., • Collaborating closely with Applied Scientists and Machine Learning Engineers to operationalise machine learning models., • Designing data models and architectures that enable reliable, trusted and accessible data across the business., • Improving data quality, observability, lineage and monitoring capabilities across critical data products., • Supporting the delivery of media measurement, customer value, pricing and personalisation initiatives., • Optimising data processing workloads for performance, scalability and cost efficiency., • Driving best practices across software engineering, data engineering and platform development., • Providing technical leadership through design reviews, mentoring and knowledge sharing., • Working with stakeholders across Customer, Marketing and Commercial functions to turn business challenges into scalable data solutions., • Contributing to the long-term evolution of ASOS's machine learning and data capabilities. We’re interested in people who can demonstrate many of the following capabilities. If your experience doesn’t match every requirement exactly, we still encourage you to apply. • Significant experience delivering data engineering solutions within cloud-based environments., • Strong expertise in Python and experience developing production-grade data pipelines and data products., • Experience working with Databricks, Spark and distributed processing technologies., • Experience designing and operating large-scale data platforms using Azure, AWS or GCP., • Deep understanding of data modelling, data architecture and modern data engineering principles., • Experience enabling data science, analytics or machine learning workloads through robust data infrastructure., • Strong understanding of CI/CD, Infrastructure as Code, automated testing and observability practices., • Experience working with large-scale customer, marketing, commercial or behavioural datasets., • Proven ability to lead the design and delivery of complex technical solutions from concept through to production., • Experience mentoring engineers and helping shape technical direction within a team., • Strong stakeholder management and communication skills, with the ability to partner effectively with technical and non-technical audiences., • A passion for solving challenging data problems and enabling teams to make better decisions through data.Experience supporting machine learning platforms, MLOps or model operationalisation., • Experience with pricing, marketing analytics, recommendation systems or customer analytics., • Experience working in eCommerce, retail or consumer-facing digital businesses. BeneFITS' • Employee discount (hello ASOS discount!), • Employee sample sales, • 25 days paid annual leave + an extra celebration day for a special moment, • Discretionary bonus scheme, • Private medical care scheme, • Flexible benefits allowance - which you can choose to take as extra cash, or use towards other benefits, • Opportunity for personalised learning and in-the-moment experiences that enable you to thrive and excel in your role #J-18808-Ljbffr

We’re ASOS, the online retailer for fashion lovers all around the world. We exist to give our customers the confidence to be whoever they want to be, and that goes for our people too. At ASOS, you’re free to be your true self without judgement, and channel your creativity into a platform used by millions. But how are we showing up? We’re proud members of Inclusive Companies, are Disability Confident Committed and have signed the Business in the Community Race at Work Charter and we placed 8th in the Inclusive Top 50 Companies Employer list. Everyone needs some help showing up as their best self. Let our Talent team know if you need any adjustments throughout the process in whatever way works best for you. We're looking for a Senior Machine Learning Engineer to join our Search & Recommendations team, where we're building the machine learning systems that help millions of customers discover products every day. Sitting within ASOS's Search & Recommenders area, the team is responsible for the recommendation, ranking and personalisation systems that sit at the heart of the customer journey. From surfacing the most relevant products and outfits to powering personalised shopping experiences, our work directly influences how customers discover and shop fashion on ASOS. You'll work on large-scale machine learning systems that power experiences such as Similar Items, People Also Viewed and personalised customer journeys that adapt in real time. Leveraging signals from millions of customer interactions, we use recommendation systems, ranking models, deep learning and emerging AI technologies to connect customers with the products they're most likely to love. As a Senior Machine Learning Engineer, you'll play a key role in designing, building and operating production machine learning systems at scale. Working alongside Applied Scientists, Machine Learning Engineers, Software Engineers and Product Managers, you'll help turn innovative ideas into reliable, high-performing systems that deliver measurable customer and commercial impact. This is an opportunity to tackle challenging problems across recommendation systems, search, ranking, personalisation and deep learning, while helping shape the future of machine learning at ASOS. • Work as part of a cross-functional team designing, building and improving machine learning systems that power search, ranking and recommendation experiences., • Collaborate closely with Applied Scientists and engineers to develop and deploy machine learning solutions that deliver measurable customer and commercial value., • Build, deploy and maintain batch and real-time machine learning models in production environments., • Contribute to recommendation, ranking and personalisation capabilities that support millions of customer interactions each day., • Continuously improve our systems, codebase and engineering practices while contributing ideas for new features and capabilities., • Support and mentor other engineers through coaching, knowledge sharing and technical collaboration., • Contribute to the team's technical direction and help evolve machine learning standards, best practices and ways of working across the wider ML community. We're interested in candidates who bring experience in several of the following areas. You'll likely be someone who enjoys combining strong software engineering fundamentals with machine learning expertise and is excited by the challenge of building reliable, scalable systems that deliver real-world impact. You may come from a recommendation systems, search, ranking, personalisation, deep learning or broader machine learning background. Most importantly, you'll enjoy solving complex technical problems, collaborating across disciplines and helping bring machine learning products from experimentation into production. • Experience applying machine learning and deep learning techniques in production environments., • Experience using deep learning frameworks and distributed computing technologies to build and deploy large-scale machine learning models., • Experience working with distributed training infrastructure, GPU-based training environments and parallelisation approaches., • Strong understanding of software engineering principles, development lifecycles and MLOps practices., • Experience developing reliable, scalable machine learning systems in production., • Comfortable providing technical leadership, mentoring and support to other engineers., • Strong collaboration and communication skills, with the ability to work effectively across engineering, science and product teams., • Employee discount (hello ASOS discount!), • Employee sample sales, • 25 days paid annual leave + an extra celebration day for a special moment, • Discretionary bonus scheme, • Private medical care scheme, • Flexible benefits allowance - which you can choose to take as extra cash, or use towards other benefits, • Opportunity for personalised learning and in-the-moment experiences that enable you to thrive and excel in your role #J-18808-Ljbffr

Location: Oxford or London (Hybrid) The Mission: Why We Exist Genomics is a science-led transatlantic TechBio combining large-scale genetic and health data with proprietary analytics to accelerate drug discovery and advance predictive, preventative healthcare. We are united by a single vision to help people live longer healthier lives, using the power of genomics. Genomics aims to help people live longer, healthier lives in two ways: super-charging drug discovery and development for novel treatments with our AI-enabled advanced genetic analytics platform, and by helping people understand their personal risk of common chronic diseases through polygenic risk scores - giving doctors and health systems the chance to get the right people into the right prevention, screening and treatment programmes at the right time. We’re looking for an exceptional Data Scientist with a strong background in human genetics and genomics, and advanced skills in data science, statistics and computational analysis. You might be a great fit for this role if you’re a methods-oriented domain specialist within the broad field of genomics with some exposure to software engineering practices and an interest in developing that side of your skillset. The primary purpose of the role is to develop and integrate support for processing, quality control and analysis of new types of data into our production and research software tools. You’ll join a team of experts in human genetics, data science and software engineering, building the platform at the heart of our Life Sciences work – helping us derive new insights into human biology and guide drug development towards safer, more effective targets. How your time splits across data processing workflows, statistical methods and software engineering will reflect your own balance of scientific and computational strengths, with an emphasis on genetics domain expertise and data analysis, including processing and interpreting functional genomics data. This role can be hired at IC2 (Data Scientist) or IC3 (Senior Data Scientist) level, depending on your experience. At IC3, you’ll operate with greater autonomy, hold a broader scientific scope, bring deeper subject-matter expertise, and lead analyses that integrate multiple genomic data sources, working with cross-disciplinary teams to deliver value. At the heart of this role is the opportunity to expand and improve how we use data and cutting edge methods to identify and validate effective and safe drug targets via deeper understanding of disease mechanisms. Identify innovative uses of new types of data for integration into our data and analytics platform. E.g from functional genomics and perturbation screens, molecular profiling and expression atlases, genomic and functional annotations, and curated interaction, pathway and ontology resources. Implement production quality code for processing, transforming and quality control of new data types for integration into our larger data model Contribute to and implement statistical and machine learning methods to a high standard of robustness, validation and reproducibility. Contribute to internal and external presentations and publications arising from our work. Keep your knowledge current on innovation and good practice in genomics, functional genomics and statistical genetics. At Senior (IC3) level, you’ll also lead projects that integrate multiple functional genomics and genetic data sources, coordinating with cross-disciplinary teams to deliver value. Strong knowledge of human genetics and functional or clinical genomics, and the ability to apply it to research questions. Skilled at analysing and learning from large-scale biological datasets, including statistical and machine learning methods. Experienced processing and interpreting data from functional genomics, molecular and expression atlases, genomic annotations, and curated pathway and interaction resources, including quality control. Competent writing code in Python and/or R for data analysis, with an appreciation of good software development practice. Comfortable using LLM programming assistants appropriately within a research analysis environment. Experienced running tools and workflows in a scalable system, for example Linux based HPC environments or on cloud systems. Experience working on a collaborative codebase using version control and CI/CD. Experience working in remote, cloud-based environments, e.g. AWS. Prior experience working in a team, ideally in an industry setting. A PhD or postgraduate degree in genetics, genomics, computational biology or bioinformatics, or statistics and machine learning applied in these fields. Your Package We are committed to providing a transparent, supportive, and rewarding work environment. Competitive Salary: Salaries are externally benchmarked annually to ensure competitive compensation. Clear Career Path: A straightforward, open progression framework means you’ll always know the path to promotion and how to achieve your next career goal. Continuous Learning: Including external courses and a wide library of L&D materials, because your growth is our success. Holiday: 25 days annual leave, plus bank holidays, plus an extra 3-day company-wide shutdown at year-end. Financial & Health Security: Robust benefits including a market-leading pension scheme, comprehensive private health insurance for you and your family with NO excess, critical illness, and life assurance. Enhanced Leave: Enhanced paid family leave to support all new parents. Flexible Working: Hybrid Working (e.g., From our London, Oxford Office) Truly Inclusive Time Off: Our 'Bank Your Bank Holiday' program allows you to exchange public holidays for dates that hold personal or cultural significance to you. Vibrant Social Culture: From regular Town Halls and team picnics to organised sports events, our social committee ensures frequent opportunities to connect and celebrate. Green Commute: Cycle-to-Work scheme and convenient office locations near major transport hubs. Ready to Build the Future? If this opportunity excites you, We are dedicated to creating a diverse environment and are proud to be an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. Genomics politely requests no contact from recruitment agencies. We do not accept speculative CVs from recruitment agencies nor accept the fees associated with them. #J-18808-Ljbffr

We power people’s progress. At Preply, we’re all about creating life‑changing learning experiences. We help people discover the magic of the perfect tutor, craft a personalised learning journey, and stay motivated to keep growing. Our approach is human‑led, tech‑enabled - and it’s creating real impact. We power people’s progress. At Preply, we’re all about creating life‑changing learning experiences. We help people discover the magic of the perfect tutor, craft a personalised learning journey, and stay motivated to keep growing. Our approach is human‑led, tech‑enabled - and it’s creating real impact. We’ve just reached unicorn status with a $150M Series D, accelerating our vision to transform education through human‑led, AI‑enhanced learning. Today, 100,000+ tutors teach 90+ languages to learners in 180 countries - and we’re only getting started. As a category‑defining company, we’re shaping what the future of learning looks like at global scale. Every Preply lesson sparks change, fuels ambition, and drives progress that matters. Joining Preply means helping define the future of education at global scale, and building something that truly matters for millions of people, every day. AI Platform provides the shared foundations that help teams across Preply build, ship, and operate AI capabilities safely at scale. The area includes ML Platform, GenAI Platform, and Agentic Platform. You will lead GenAI and Agentic Platform: approximately 8-12 engineers across two teams, while partnering closely with ML Platform leadership. GenAI Platform owns shared model access, routing, evaluation, observability, prompt and configuration lifecycle, retrieval, grounding, and guardrails. Agentic Platform builds on those foundations with durable execution, tools, state, context, memory, permissions, human controls, agent evaluation, and runtime safety. The two teams share a Product Manager. Together, you will shape strategy, priorities, adoption, and outcomes; clarify what belongs in shared infrastructure versus product teams; and evolve the platform as models, frameworks, and company needs change. Learn more through our Engineering Blog, Tech Radar, and YouTube channel. GenAI and Agentic AI are central to Preply's AI strategy. As the Senior Engineering Manager for GenAI & Agentic Platforms, you'll own the engineering strategy, execution, and organizational health of two complementary teams that take AI workloads from experimentation to reliable production systems. This is a multi‑team leadership role for a manager with strong technical judgment. You won't be the primary implementer, but you'll go deep on architecture and production AI, coach senior engineers, shape platform abstractions and operational standards, and partner with Product, Applied Science, Data, Security, and Engineering teams. • Set the long‑term engineering vision for GenAI Platform and the Agentic Platform, ensuring they operate as a single, coherent platform., • Partner with the Product Manager across both teams to define outcomes, prioritize investments, and measure the impact of the platforms., • Lead and develop approximately 8-12 engineers across two teams through clear expectations, direct feedback, performance management, career growth, and coaching., • Own hiring quality, team composition, evolving team boundaries, and operating models as the platforms and company change., • Guide architecture across model access, evaluation, observability, retrieval, agent orchestration, tools, state, memory, permissions and control planes., • Translate strategy into realistic plans, balancing foundational investment with near‑term product needs while surfacing trade‑offs and maintaining speed, quality, and predictability., • Align senior stakeholders across Product, Applied Science, Data, Security and Engineering on platform standards, build‑vs‑buy decisions and shared priorities., • 8+ years of software engineering experience, including 5+ years in engineering management and experience leading multiple teams or a multi‑squad technical area., • A track record of hiring, coaching, and retaining high‑performing teams., • Strong technical depth in platform engineering, backend or distributed systems, ML infrastructure or developer infrastructure., • Practical experience with production GenAI or Agentic systems and the ability to reason about model access, evaluation, observability, retrieval, agent orchestration, tool use, state, permissions, reliability, cost, and safety., • AI Expertise: You use Agentic AI beyond code generation to support architecture, planning, and decision‑making, while retaining human judgment for architecture, people decisions, business logic, and security, and establishing quality gates and safety nets for team workflows., • Experience leading platform products, with a strong instinct for self‑service, API design, developer experience, adoption and avoiding unnecessary complexity., • Clear communication and stakeholder leadership, with the ability to align teams with different incentives, make sound decisions with incomplete information and revisit assumptions as the ecosystem changes., • Experience managing teams that built AI or ML platforms used by multiple teams., • Experience with agent frameworks or durable workflow technologies such as LangGraph, OpenAI Agents SDK, or Temporal., • Hands‑on familiarity with GenAI evaluation and observability, prompt or model lifecycle, retrieval systems, multi‑provider routing or open‑model serving., • Experience making build‑vs‑buy decisions without locking the organization into one provider or framework., • Experience measuring platform success through adoption, customer outcomes, and engineering leverage rather than infrastructure delivery alone., • An open, collaborative, dynamic, and diverse culture;, • A generous monthly allowance for lessons on Preply.com, Learning & Development budget, and time off for your self‑development;, • A competitive financial package with equity, leave allowance and health insurance;, • Access to free mental health support platforms;, • Access to Gympass‑partnered wellness and gym centers throughout London to promote and support well‑being and physical health;, • The opportunity to unlock the potential of learners and tutors through language learning and teaching in 175 countries (and counting!)., • Care to change the world - We are passionate about our work and care deeply about its impact to be life changing., • We do it for learners - For both Preply and tutors, learners are why we do what we do. Every day we focus on empowering tutors to deliver an exceptional learning experience., • Keep perfecting - To create an outstanding customer experience, we focus on simplicity, smoothness, and enjoyment, continually perfecting it as every detail matters., • Now is the time - In a fast‑paced world, it matters how quickly we act. Now is the time to make great things happen., • Disciplined execution - What makes us disciplined is the excellence in our execution. We set clear goals, focus on what matters, and utilize our resources efficiently., • Dive deep - We leverage business acumen and curiosity to investigate disparities between numbers and stories, unlocking meaningful insights to guide our decisions., • Growth mindset - We proactively seek growth opportunities and believe today's best performance becomes tomorrow's starting point. We humbly embrace feedback and learn from setbacks., • Raise the bar - We raise our performance standards continuously, alongside each new hire and promotion. We build diverse and high‑performing teams that can make a real difference., • Challenge, disagree and commit - We value open and candid communication, even when we don’t fully agree. We speak our minds, challenge when necessary, and fully commit to decisions once made., • One Preply - We prioritize collaboration, inclusion, and the success of our team over personal ambitions. Together, we support and celebrate each other's progress. Preply.com is committed to creating an inclusive environment where people of diverse backgrounds can thrive. We believe that the presence of different opinions and viewpoints is a key ingredient for our success as a multicultural Ed-Tech company. That means that Preply will consider all applications for employment without regard to race, color, religion, gender identity or expression, sexual orientation, national origin, disability, age or veteran status. #J-18808-Ljbffr

Our client is a leading international bank. Who is our Innovation Banking? Our Innovation Banking is the power behind the UK's forward-thinkers, future-makers, and leap-takers, helping them ignite the bold ideas that reshape our world. We offer flexible banking solutions for start-ups, scale-ups, growth businesses, investors and those working towards IPO typically within the technology and life science sectors. Whether it's comprehensive banking, managing cashflow, plans for buyouts or Strategic Fund Solutions, we power ideas at every stage of their journey. From the first-time founders to the funds that back them, and everything in between. We're proud to accelerate growth for our clients, create meaningful connections and communities, and open a world of global opportunity for entrepreneurs and investors alike. Here's to never standing still. Come and join us! The team you'll work with: The Head of Transactional Credit is a leadership role reporting to the Head of Growth & Financing. The role is responsible and accountable for leading the Transactional Credit Team (TCT) to ensure timely, accurate and well-controlled execution of client transactional credit requests, ensuring strong risk discipline and adherence to policy and process. In parallel, the role also owns the delivery and management of our Associate Development Programme (ADP), including workforce planning, recruitment, onboarding, training, rotation allocation and day-to-day oversight of Associate cohorts to build a strong, diverse talent pipeline aligned to business needs. The value you'll add: The role holder will work closely with Relationship Management teams, Debt Finance, and Credit Risk partners to ensure client needs are met efficiently through TCT and ADP while maintaining our client's risk culture and conduct expectations. A typical day may include prioritising and reviewing live client limit requests, removing execution blockers, coaching team members, aligning on risk and credit requirements with partners, planning Associate rotations with business heads, and ensuring a consistent, high-quality ADP experience across the programme. What you can expect to be doing: Transactional Credit Team (TCT) – execution, control and client outcomes Leads a small team of TCT colleagues, setting clear direction and ensuring effective capacity management to meet service expectations Ensures that TCT executes client limit and transactional credit requests effectively, adhering to agreed process, documentation standards, and relevant policy requirements Maintains strong risk discipline across all requests, ensuring appropriate controls are embedded, understood and consistently applied; escalates issues and exceptions promptly and transparently Partners closely with Relationship Management teams, Debt Finance and Credit Risk to align on client priorities, structure considerations, credit appetite and approvals, and to drive timely end-to-end execution Supports initiatives to drive wallet share through the provision of transaction banking credit products Monitors workflow and outcomes (e.g., timeliness, quality, rework themes), using insights to improve execution, reduce friction, and strengthen control effectiveness Associate Development Programme (ADP) – talent pipeline, programme delivery and colleague development Owns planning for the ADP, including cohort sizing, intake timing, onboarding approach, training plan and rotation allocation, in close partnership with the business Partners closely with the business to identify future FTE needs and works with Staffing to source and secure diverse top talent for the programme Oversees ADP Associates day-to-day, providing guidance and coaching; manages workload where required; drives skills development, career development, and provides ongoing feedback to support performance and progression Works closely with team heads across the business to ensure a consistent ADP experience and that Associate learning objectives are met whilst on rotation Ensures regular structured feedback is received from rotation teams regarding Associates, and uses it to improve the programme and address development needs early Requirements: Credit underwriting and portfolio management experience in a commercial banking environment, preferably with knowledge of the Innovation Economy Ability to coach and develop less experienced staff members, enabling improved efficiency and effectiveness Able to proactively manage stakeholders and business partners across Relationship Management, Debt Finance, Credit Risk and enabling functions Able to effectively manage resources to optimise process, throughput and outcomes while maintaining control standards Excellent communication skills (written and verbal), with the ability to simplify complex issues and align partners quickly High attention to detail, with a consistent focus on quality of execution and documentation Where you'll be based: Our home office in Finsbury Square, London. We offer hybrid working to our employees, so you can flex between home and the office, with a current requirement to be in the office 2 days per week. Being open to different points of view is important for our business and the communities we serve. We're dedicated to creating diverse and inclusive workplaces - no matter their gender, ethnicity, disability, religion, sexual orientation, socio-economic background or age. We are committed to removing barriers and ensuring careers at our client are inclusive and accessible for everyone to be at their best. We take pride in being a Disability Confident Leader and will offer an interview to people with disabilities, long term conditions or neurodivergent candidates who meet the minimum criteria for the role. If you have a need that requires accommodations or changes during the recruitment process, please get in touch with our Recruitment Helpdesk via . TPBN1_UKTJ

An exciting opportunity has arisen to join an expanding interactions analytics solution provider within the contact centre space, with a particular focus on enterprise level sales in speech / text analytics and workforce optimisation (WFO). As an integral part of the clients Sales Team, a Solutions Architect is accountable for technical and analytical pre‑sales activities to facilitate and drive a successful sales process. We are looking for an experienced pre‑sales solution architect / engineer tyre individual with a proven track record of enterprise level contact centre analytics solutions sales with a strong bias towards interaction analytics solutions. Please note this is a home based role with travel required - YOU DO NOT NEED TO LOCATED IN LONDON / SOUTH EAST • Assisting in achievement of 100% and above of sales targets, • Development of strong relationships with prospects enabling the sales of the client’s products and services, • Contribute to team success by partnering with sales directors to develop specific strategy and objectives related to each prospect, • Leading the product and technical presentation phases of the client’s solution, • Demonstrating how the client’s solution enables customers to achieve ROI, • Providing pre‑sales technical assistance and product education, • Conducting the proof of concept including technical setup, content creation, and data analytics to develop ROI stories which are presented back to prospects, • Assisting in the development of product demonstrations, • Assisting in the technical / product / functional response areas of RFP/RFI/RFQ requests, • Coordinating with technical/products experts to engage with prospects when appropriate, • Producing support material for the sales team, • Recording and maintaining client contact data, • Conveying prospect/customer requirements to Product Management teams, • Assisting in marketing activities related to shows, seminars and conferences, • Well‑rounded pre‑sales analytics, background with minimum of 3+ years of experience in speech and text analytics solutions, • Comfortable in the dynamic atmosphere of an entrepreneurial organization with aggressive sales goals., • Strong presentations skills with an ability to explain technical / functional concepts to a non‑technical / business audience., • Must have the ability to understand and convey how specific technology can be applied to solve business issues., • Must have the ability to communicate professionally and effectively in written responses to emails, RFPs, etc., • Must be able to work independently and with fellow team members., • Ability to develop and interpret data analysis for the purpose of conveying the value of a technical/software solution., • Comfortable with technology and ability to quickly learn new technologies, serving as a SME on the client solution., • Ideally A degree, preferably in Business, Linguistics, Computer Science or related field., • Ability to travel (50%+) for prospect/customer meetings, company gatherings, and industry conferences., • Pass standard background check for PCI Compliance security clearance. #J-18808-Ljbffr

Wood Mackenzie is the global leader in analytics, insights and proprietary data across the entire energy and natural resources landscape. For over 50 years our work has guided the decisions of the world’s most influential energy producers, utilities companies, financial institutions and governments. Now, with the world’s energy system more complex and interconnected than ever before, sector-specific views are no longer enough. That’s why we’ve redefined what’s possible with Intelligence Connected. By fusing our unparalleled proprietary data with the sharpest analytical minds, all supercharged by Synoptic AI, we deliver a clear, interconnected view of the entire value chain. Our trusted team of 2,700 experts across 30 countries breaks siloes and connects industries, markets and regions across the globe. This empowers our customers to identify risk sooner, spot opportunities faster and recalibrate strategy with confidence – whether planning days, weeks, months or decades ahead. Wood Mackenzie Intelligence Connected • Inclusive – we succeed together, • Trusting – we choose to trust each other, • Customer committed – we put customers at the heart of our decisions, • Future Focused – we accelerate change, • Curious – we turn knowledge into action We are seeking a full-time Power Market Analyst to join Wood Mackenzie’s Power & Renewables team, focusing on the development and application of advanced power market models across European electricity markets. As a Power Market Analyst, you will play a key role in building, maintaining, and enhancing market optimization models used to analyse power systems, generation economics, transmission constraints, and market outcomes. You will apply linear programming (LP) and other optimization techniques to simulate market behaviour, assess investment and operational decisions, and provide actionable insights on power market dynamics, decarbonization pathways, and energy transition challenges. • Develop, maintain, and enhance optimization-based power market models for European electricity markets., • Design and implement LP and mixed-integer optimization models to simulate generation dispatch, storage operation, cross-border trading, and market-clearing mechanisms., • Analyse power market fundamentals, including supply-demand dynamics, renewable integration, fuel markets, emissions costs, and transmission constraints., • Conduct scenario analysis to evaluate market outcomes, asset profitability, policy impacts, and energy transition pathways., • Translate complex model outputs into clear market insights and recommendations for internal stakeholders and clients., • Improve model methodologies, assumptions, and analytical frameworks to enhance model accuracy, transparency, and performance., • Work with large datasets and develop efficient data workflows to support model development and analysis., • Collaborate with experts across power markets, renewable energy, economics, and policy to deliver high-quality research and market intelligence., • Monitor developments in European energy markets, regulatory frameworks, and market design, assessing their impact on market participants and investment decisions., • Support client engagements through presentations, bespoke analyses, technical discussions, and thought leadership. We are looking for a highly analytical and intellectually curious individual with a strong foundation in optimization, quantitative modelling, and power market analysis. You enjoy solving complex problems, building robust models, and generating insights that support strategic decision-making. • A degree in Operations Research, Engineering, Applied Mathematics, Economics, Energy Systems, Computer Science, or a related quantitative discipline., • Experience in electricity market analysis, power system modeling, or energy economics., • Strong knowledge of optimization techniques, particularly linear programming (LP) and mixed-integer programming (MIP)., • Experience developing and implementing mathematical models for power systems, generation portfolios, storage assets, or electricity markets., • Proficiency in Python and/or other programming languages used for optimization and quantitative analysis., • Experience with optimization frameworks and solvers such as Gurobi, CPLEX, Xpress, Pyomo, or similar tools., • Strong understanding of European power market fundamentals, market design, and price formation mechanisms., • Ability to analyze complex datasets and communicate technical findings clearly to both technical and commercial audiences., • Strong problem-solving skills, attention to detail, and ability to manage multiple projects simultaneously., • Excellent verbal and written communication skills in English. Why Join Us? At Wood Mackenzie, you will work on industry-leading power market models that help clients navigate rapidly changing energy markets and the transition to a low-carbon economy. You will collaborate with leading analysts, modelers, and industry experts to solve complex challenges facing power systems, renewable integration, energy storage, and electricity market design. This role offers an opportunity to apply cutting-edge optimization techniques and market analysis to inform investment decisions, support policy evaluation, and shape the future of the energy sector. We are an equal opportunities employer. This means we are committed to recruiting the best people regardless of their race, colour, religion, age, sex (including pregnancy, sexual orientation, and gender identity), national origin, disability or protected veteran status. You can find out more about your rights under the law at www.eeoc.gov #J-18808-Ljbffr

Location: London, England, United Kingdom • Lead engineering architecture design reviews, incorporating AI-driven insights and system modeling, • Set a high technical bar through code and architecture reviews, including evaluation of AI-generated code and patterns, • Mentor engineers on scalable system design and AI-first development practices, • Drive adoption of AI-assisted development tools and workflows across the engineering organization, • Work across teams with Product, Design, and Engineering to create integrated solutions, • Improve engineering processes by embedding automation, AI tooling, and intelligent workflows into planning and execution, • Build services that adhere to high standards on availability and latency in a mission-critical environment, • Leverage AI systems to optimize performance, observability, and operational efficiency, • Bachelor's Degree in Computer Science, Engineering, or related field, • 6+ years of professional software development experience, • Experience designing and delivering highly-available, scalable cloud-based systems, • Backend service experience in multiple managed languages such as Java, Scala, Go, C#, or similar, • Experience with SQL or NoSQL data stores, • Experience evaluating and integrating AI-assisted development tools into engineering workflows, • Strong understanding of how AI can be applied to improve developer productivity, system design, and operational efficiency, • Competitive base salary and RSUs, • Comprehensive pension plan with matching contribution, • Private health insurance & cash plans, • 30 days paid holiday + UK public holidays, • Enhanced maternity/paternity leave, • Life assurance & income protection, • Career growth support and wellness resources We are an equal opportunity employer that promotes justice, advances equity, values diversity and fosters inclusion. We’re committed to hiring the best talent — regardless of race, creed, color, ancestry, religion, sex (including pregnancy), national origin, sexual orientation, age, citizenship status, marital status, disability, gender identity, genetic information, veteran status, or any other characteristic protected by applicable laws, regulations and ordinances — and empowering all of our employees so they can do their best work. Don’t meet every single requirement? That's ok. At Axon, we Aim Far. We think big with a long-term view because we want to reinvent the world to be a safer, better place. We are also committed to building diverse teams that reflect the communities we serve. Studies have shown that women and people of color are less likely to apply to jobs unless they check every box in the job description. If you’re excited about this role and our mission to Protect Life but your experience doesn’t align perfectly with every qualification listed here, we encourage you to apply anyways. You may be just the right candidate for this or other roles. #J-18808-Ljbffr

You enjoy working on complex data problems whilst being able to suggest simple (yet effective) solutions. You are comfortable working with uncertainty and like to make things clearer. You’re passionate about technology and keep up as it evolves. You focus on the future and thrive most when solving problems. Client’s love working with you. You are honest and do things when you say you will, you also know how to explain things clearly and concisely. You can educate and inspire. You’ve got a background in data science, machine learning algorithms, data analytics, and data engineering along with their technologies. You’re equally comfortable presenting to clients, providing advice or building prototypes. You’re a collaborator and enjoy stepping out of your role from time to time, whether it’s to support your clients, colleagues or to learn something new. • Leading client projects and providing subject matter expertise., • Working in scrum-like environments for iterative and ‘fail-fast’ work and innovation., • Working in cross-disciplinary teams., • Working at the PoC (proof-of-concept) stage through to MVP and MMP stages., • Assessing your clients’ business and technical needs with the ability to identify opportunities for data science to be used. Managing client and stakeholder relationships appropriately., • Solving problems using data science techniques and in a scientifically robust fashion., • Identifying data sources that are relevant to client needs, and related data science concepts that leverage those sources to aid the client., • Working with various forms of data (e.g., unstructured, semi-structured or structured; text, time-series or image) and suitably modelling them (e.g., table, key-value pair, graph) for efficient data science use., • Investigating and analysing data to see ‘the wood from the trees’ and drilling down to the ‘whys’ of the data., • Applying statistical and evidence-based techniques to inform insights and actions from the data., • Communicating technical content at the right pitch/level both internally and to customers., • Presenting to the client, using data science tooling and investigation, a ‘story’ of the data., • Building maintainable code that use existing data science libraries, implement existing data science techniques, or implement novel techniques., • Designing, evaluating, and implementing on-premise, cloud-based and hybrid data science and machine learning techniques and algorithms (including providing relevant review and guidance on testing aspects, identification of risks and proposing and implementing their mitigations)., • Developing scalable models and algorithms that can be deployed into production environments., • Applying ethical principles in handling data., • Accurately delivering high quality work to agreed timelines and taking the initiative and knowing how to jump straight in., • Supporting client engagements, including pitches and presentations., • Helping to support & grow Daintta by actively inputting into the company strategy and helping to shape our future., • Representing us and our core values: transparent, fair and daring, • You have 5+ years of degree level industry experience in data science., • You have extensive degree level experience in a STEM subject., • You have experience of working in a consultancy, engineering, or data industry., • You have led client delivery across a range of projects, e.g., data science, data analytics, data engineering, data intelligence, data security and proven experience in relevant technologies (e.g., Python applied to data science), as anindividual-contributor and leading a small team., • You have experience working on cloud-based infrastructure (e.g., AWS, Azure,, • GCP).You have demonstrable continuous personal development., • You have strong interpersonal skills, • You have experience with using CI/CD tooling to analyse, build, test and deploy your code and proven experience in their technologies., • You have experience in database technologies (e.g., SQL, NoSQL such as Elasticsearch and Graph databases), • You have a good understanding of coding best practices and design patterns and experience with code and data versioning, dependency management, code quality and optimisation, error handling, logging, monitoring, validation and alerting. Hybrid, with 2-3 days working from Daintta office (London or Cheltenham) or on client site as required. In addition to being rewarded fairly for your contribution to the business, you get to work in a dynamic organisation that is agile and responsive. A business that is growing fast and where you get to drive and shape the future. A place where you are respected by everyone and your voice is important. Somewhere where you can be innovative and creative. A place where you have the opportunity to learn about all aspects of business from marketing to sales, to delivery and business operations. We are Daintta. We provide deep expertise with technical and business specialists to help clients and organisations secure and protect the UK. In complex environments, we use innovative methods to solve the hardest data challenges to help organisations make more informed and accurate decisions, at scale and faster. We are agile, responsive, independent, and collaborative while our values of Fair, Transparent and Daring guide all our decision making. Due to the nature of this position, you must be willing and eligible to achieve a minimum of SC clearance. To qualify, you must be a British Citizen and have resided in the UK for the last 5 years. For more information about clearance eligibility, please see government/organisations/united-kingdom-security-vetting #J-18808-Ljbffr

This role designs, implements, and evolves a highly available global financial network spanning data centres, trading floors, and enterprise sites. You will lead network design and delivery work — new builds, platform refreshes, and third-party service turn-ups — while acting as senior technical escalation for complex network issues. The role suits an engineer with excellent data centre and enterprise network fundamentals, a solid understanding of EVPN and VXLAN on Arista, a strong drive to automate manual processes, and an interest in applying AI tooling creatively to operational problems. • Design and implement data centre and enterprise network solutions, including new installations, platform refresh and redesign, and site migrations, • Deliver network projects end to end: design documentation, build, testing, cutover, and handover to operations, • Turn up and support services to third parties, including CDN, extranet services, and VPNs, • Lead routing and switching design and configuration across Juniper, Arista, and Cisco platforms, covering BGP, OSPF, EIGRP, route manipulation, redistribution, and filtering, • Design, build, and support EVPN/VXLAN data centre fabrics on Arista platforms, • Act as senior escalation for complex network incidents, contribute to root cause analysis, and drive permanent resolutions, • Build network automation and tooling (Python, Ansible) to remove manual effort, and apply AI creatively to monitoring, troubleshooting, and operational problems, • Work with and refine enterprise monitoring solutions so monitoring and alert coverage keeps pace with the estate, • Maintain infrastructure hygiene through code upgrades, EOL hardware replacement, and network audits, • Keep design and support documentation accurate for internal and customer support teams, • Implement BAU changes in accordance with the change management process (break fix, moves, adds, and changes), • Mentor junior engineers and analysts, and ensure smooth handover of network issues between regions, • Strong routing and switching design and implementation experience across Junos, Arista EOS, and Cisco IOS, including EIGRP, OSPF, and BGP, • Solid understanding of EVPN and VXLAN, with hands‑on design and implementation experience on Arista platforms, • Excellent data centre and enterprise network fundamentals, from design through implementation and operation, • Hands‑on experience with Palo Alto firewalls and F5 load balancers, • Strong understanding of Wi‑Fi networking principles, including design, installation, maintenance, and troubleshooting, • Scripting and automation experience (Python, Ansible, or similar) applied to real network problems, • Resilient under pressure, with a proactive, solutions‑focused approach to incident management, • Good communicator, both written and verbal, with strong time management and prioritisation of workload, • Curious, creative approach to applying AI tools to improve network operations, monitoring, and troubleshooting, • Cisco CCNP Routing & Switching, • Wireless foundational certification (required), • Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience, • Experience supporting a high‑volume, high‑availability financial trading environment, • Experience of low‑latency network design or multicast market data, • Extreme Networks platform experience, • Exposure to network-as-code, source‑controlled network configuration, or CI/CD for network changes, • Experience with cloud networking or hybrid connectivity (GCP, AWS, Azure), • Familiarity with SD‑WAN, network segmentation, or zero‑trust network models, • Routing and switching: Juniper Junos, Arista EOS, Cisco IOS, • Security and load balancing: Palo Alto, F5, • Wireless: Extreme Networks or similar enterprise Wi‑Fi platforms, • Automation and scripting: Python, Ansible, Git, • Monitoring: enterprise network monitoring and alerting platforms, Grafana, Splunk, • Service management: ServiceNow, Jira, Confluence, • AI tools and chatbots such as Claude, ChatGPT and Microsoft Copilot Cantor Fitzgerald, founded in 1945, is a premier global financial services and technology firm with a presence in over 30 countries and more than 14,000 employees worldwide. Renowned for innovation, scale, and deep expertise across capital markets, Cantor Fitzgerald delivers cutting‑edge solutions to institutional clients including banks, hedge funds, trading firms, and corporations. As one of the few remaining private partnerships on Wall Street, Cantor Fitzgerald combines entrepreneurial agility with long‑term vision—offering leadership in Equity and Debt Capital Markets, Sales & Trading, SPAC underwriting, Structured Products, Prime Brokerage, Asset Management, and Commercial Real Estate Services. If you’re looking to join a firm that values resilience, innovation, and client focus, Cantor Fitzgerald offers an exceptional platform to make an impact in shaping the future of global financial markets. #J-18808-Ljbffr

Enterprise Architect — Artificial Intelligence AI/ML Infrastructure, Platform & Governance World Wide Technology is looking for a deeply technical Enterprise Architect who will own the delivery of AI projects end to end from the silicon and data center design that underpins AI workloads, through the software and MLOps stack, to the governance frameworks that make AI trustworthy and defensible at scale. This is a technical hardware-and-software architect role, not a strategy-only position. The successful candidate operates comfortably across GPU infrastructure, high-performance networking, model training and inference pipelines, and the AI risk/governance disciplines increasingly demanded by regulators and enterprise boards. The Enterprise Architect will lead technical delivery teams for client engagements, acting as the single point of technical accountability from design through to go-live, while mentoring delivery teams and shaping WWT's broader AI point of view. • Own end-to-end technical delivery of AI/ML engagements: architecture definition, design authority, build oversight, and go-live validation., • Host and chair Architecture Review Board (ARB) and Technical Design Authority (TDA) sessions for AI engagements, owning governance gates, decision records, and design sign-off., • Architect AI infrastructure spanning GPU/accelerator compute, high-performance interconnects ,parallel/high-throughput storage, and orchestration, • Design the AI software stack: training and fine-tuning pipelines, distributed training frameworks, inference/serving platforms, MLOps/LLMOps tooling, vector databases, and retrieval-augmented generation (RAG) and agentic architectures., • Define and AI governance frameworks covering model risk management, responsible AI, data lineage, bias/fairness testing, explainability, and regulatory alignment (EU AI Act, NIST AI RMF, ISO/IEC 42001)., • Act as trusted technical advisor to client CTOs, CIOs and Heads of Data/AI on platform strategy, build-vs-buy decisions, and AI operating model design., • Lead technical workshops, architecture design sessions, and proof-of-concept builds with cross-functional engineering, data science, and security teams., • Serve as the technical escalation point for delivery teams; unblock design and implementation issues under time pressure., • Mentor other architects and engineers on AI systems design, uplifting AI depth across the practice., • Partner with sales and pre-sales to scope AI solutions, size infrastructure, and validate technical feasibility of proposed architectures., • Define automation, orchestration, and observability standards across the AI stack, from GPU cluster provisioning through to model monitoring in production., • Architect integration points connecting AI platforms to existing enterprise networks, third-party systems, and external or service-provider-hosted environments (e.g. colocation, managed GPU-as-a-service, external inference endpoints)., • Track the fast-moving AI landscape — new model architectures, silicon, frameworks and regulation — and translate relevant developments into WWT's delivery methodology and client recommendations., • 10+ years in enterprise architecture, infrastructure engineering, or platform engineering roles., • 5+ years focused specifically on AI/ML systems design and delivery, including at least 2 years working with generative AI/LLM workloads., • Demonstrated track record leading technical delivery (not just advisory) on enterprise-scale AI or HPC infrastructure programmes., • GPU/accelerator architectures: NVIDIA / AMD, including multi-node scale-out design., • Accelerator interconnects: NVLink, NVSwitch, • High-performance networking: InfiniBand and RoCEv2 fabric design, 400G/800G Ethernet, rail-optimized topologies for AI clusters., • Data center facilities: power density, liquid cooling, and rack-level design considerations specific to AI compute., • Storage: parallel and high-throughput file systems (e.g. Everpure, WEKA, VAST, NetApp) sized for training and checkpointing workloads., • ML frameworks: PyTorch and TensorFlow at a working, hands-on level., • Distributed training: Horovod, DeepSpeed, Megatron-LM, or equivalent multi-node training frameworks., • Inference & serving: NVIDIA Triton, vLLM, TensorRT-LLM, or equivalent high-throughput serving platforms., • MLOps/LLMOps: Kubeflow, MLflow, and at least one hyperscaler ML platform (SageMaker, Azure ML, or Vertex AI)., • Generative AI: LLM fine-tuning (LoRA/QLoRA), RAG architecture design, vector databases (Pinecone, Milvus, Weaviate), and agentic frameworks (LangChain, LangGraph, Semantic Kernel)., • Data pipelines: data lake/lakehouse architectures, ETL/ELT, and data quality/lineage tooling that feed AI systems., • Infrastructure-as-code: Terraform and Ansible for repeatable, automated provisioning of GPU clusters and AI platform environments; GitOps (ArgoCD) for continuous, declarative platform delivery., • Pipeline orchestration: Kubeflow Pipelines, Apache Airflow, or Argo Workflows to orchestrate multi-stage training, fine-tuning, and inference pipelines., • Cluster & workload scheduling: Slurm, Run:ai, and NVIDIA Base Command Manager for GPU job scheduling; Kubernetes-native GPU scheduling including device plugins and MIG partitioning for multi-tenant clusters., • CI/CD/CT for ML: automated model testing, validation gates, and promotion pipelines (continuous training/continuous delivery) that move models safely from experimentation to production., • Infrastructure & GPU observability: NVIDIA DCGM, Prometheus/Grafana, and related telemetry stacks for GPU utilization, thermal, and cluster health monitoring., • Model & LLM observability: production model performance monitoring, data/concept drift detection, and LLM-specific observability (token usage, latency, cost, hallucination/quality metrics) using tools such as Arize, WhyLabs, or Langfuse., • Logging & tracing: centralized logging (ELK/OpenSearch) and distributed tracing (OpenTelemetry) across data, training, and inference pipelines for end-to-end root‑cause analysis., • Platform integration: API-based and event-driven integration of AI platforms with enterprise systems, using REST/gRPC APIs and message/event streaming platforms (e.g. Kafka)., • Enterprise network integration: designing connectivity between AI/GPU infrastructure and existing campus, data center, and WAN environments, including capacity and latency planning for east‑west training traffic and north‑south inference traffic., • Hybrid & multi-cloud connectivity: integrating on-premises AI platforms with cloud AI services via dedicated interconnects (Direct Connect, ExpressRoute) and multi-cloud/hybrid connectivity patterns for distributed training or burst inference., • Service provider & third‑party integration: experience architecting connections into external or service‑provider‑hosted environments — colocation interconnects, managed GPU-as-a-service offerings, and third‑party/external inference endpoints — including the commercial and technical boundary considerations involved., • Secure exposure of AI services: working knowledge of API gateways, service mesh, and mutual TLS as applied to exposing or consuming AI services safely across organizational and network boundaries., • Cross-functional design: proven ability to partner directly with network and security architects to define end‑to‑end integration architecture spanning AI platforms, enterprise networks, and external/customer environments., • Working knowledge of model risk management frameworks and responsible AI principles (fairness, explainability, human oversight)., • Familiarity with data privacy regulation (GDPR, CCPA) as applied to AI training and inference data., • Working knowledge of emerging AI‑specific regulation and standards: EU AI Act, NIST AI Risk Management Framework, ISO/IEC 42001., • Experience establishing model documentation, audit trail, and approval‑gate processes for production AI systems., • AI‑specific security fundamentals: model security, prompt‑injection defenses, supply chain security for open‑source/open‑weight models., • Solutions‑architect level expertise in at least one hyperscaler (AWS, Azure, or GCP), including their native AI/ML services., • Ability to design for hybrid on‑premises/cloud AI deployments, including data residency and sovereignty constraints., • Proven experience hosting and chairing formal Architecture Review Board (ARB) and Technical Design Authority (TDA) forums, including agenda ownership, decision logging, and stakeholder facilitation., • Ability to define and operate governance gates across the engagement lifecycle: design authority sign‑off, change control, and exception/waiver management for AI platform decisions., • Experience producing and maintaining architecture decision records (ADRs), design standards, and reference architectures that are actively enforced through ARB/TDA governance., • Comfortable presenting and defending architecture decisions to senior client governance bodies, including constructively challenging non-compliant or high-risk designs., • Excellent executive communication and presentation skills; able to flex between deep technical detail and C‑suite framing., • Proven ability to author low‑level design (LLD) and high‑level design (HLD) documentation to a professional services standard., • Experience running technical design workshops with senior client stakeholders and multi‑vendor delivery teams., • NVIDIA certifications (NCP‑AI Infrastructure, or NVIDIA Deep Learning Institute credentials) — strongly preferred., • Cloud AI/ML certification: AWS Certified Machine Learning – Specialty, Microsoft Certified: Azure AI Engineer Associate, or Google Professional Machine Learning Engineer — at least one preferred., • Kubernetes: CKA or CKAD — preferred., • TOGAF 9/10 or equivalent enterprise architecture certification — beneficial. Depth in the specialist area above is mandatory. Experience in the following adjacent domains is a strong plus and will be valued in candidate evaluation, since it enables broader solution ownership across engagements. • Networking and data center design (routing/switching, fabric architectures)., • Storage architecture (all‑flash arrays, software‑defined storage, parallel file systems)., • Cybersecurity architecture, particularly zero trust and data protection., • Traditional enterprise application and integration architecture., • Software development background (Python, Go, or similar) for tooling and automation., • Virtualization/private cloud platforms (VMware, OpenShift/OpenStack), given increasing convergence with AI infrastructure., • Leads technical delivery independently with minimal oversight; comfortable being the final technical authority on an engagement., • Mentors junior and mid-level architects and engineers, raising the technical bar across the team., • Builds credibility quickly with highly technical client stakeholders as well as executive sponsors., • Thrives on ambiguity in a fast-moving technology space; makes sound architectural calls with incomplete information., • Collaborates effectively across sales, pre‑sales, delivery, and partner (NVIDIA, hyperscaler, ISV) teams., • Bachelor's degree in Computer Science, Computer Engineering, or a related technical field, or equivalent demonstrable experience., • Advanced degree (MS in CS/AI/ML or related) beneficial but not required given sufficient hands‑on depth., • Continuous, demonstrable learning in AI — publications, open‑source contributions, conference speaking, or lab‑based experimentation are all valued signals. Employment decisions are made without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status or other characteristics protected by law. We are committed to working with and providing reasonable accommodations to individuals with disabilities. Applicants to and employees of most private employers, state and local governments, educational institutions, employment agencies and labor organizations are protected under Federal law from discrimination. EEO is the Law #J-18808-Ljbffr

At EY, we’re all in to shape your future with confidence. We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world. EY aspires to become the world’s most trusted AI-powered professional services firm, delivering transformative value to clients and employees. Leveraging its extensive data across finance, legal, HR, and core business operations, EY is uniquely positioned to accelerate its data strategy and unlock new opportunities for growth and protection of its business. To achieve this vision, all Service Lines and global regions must collaborate on strategic priorities aligned with EY’s “All In” goal: safeguarding the current US$50B revenue base while generating the next US$50B. Central to this effort is advancing data management across its lifecycle to enhance existing services and create innovative offerings. EY’s AI Ready Data Strategy, led by Applied Innovation and the Global Data Office, is the foundation for this transformation. The Data Office drives applied innovation by redefining how data is discovered, managed, utilized, and scaled. As we embark on a journey to be AI Ready at EY, the data office is leading a key new capability that will transform how EY and its clients use AI and Agentic technology to transform data management: ‘EY.ai Data Agents’. EY.ai Data Agents are the core trusted digital assistants of EY’s data estate. Built to perform, certified to scale, and always operating under the stewardship of EY professionals, they unlock the full potential of data across the firm. Whether it’s onboarding a client, validating entities, or orchestrating complex data flows, EY.ai Data Agents accelerate delivery, enhance trust and raise the bar for quality. Data Agents unlock EY’s data estate while keeping humans firmly in control. The Global Data Office Data team is seeking a highly skilled and experienced Data Agent owner to drive the development of the Data Agent capability. As the owner, you will be focussed on the execution of the data agent vision, working closely with EY’s innovation community, key clients and Alliance partners to build a world leading agentic capability. You will be a ‘hands on’ agentic data lead, passionate and energetic, exceptional communication and stakeholder skills. You will translate strategy into action; transforming how EY will execute data driven, AI powered services. • Develop a comprehensive Data Agent offering, including solution design, commercial models, and support structures., • Establish standards, methods, and tools to ensure consistent and scalable Data Agent development., • Define the Agentic Data Stewardship framework in collaboration with the Data Stewardship Office., • Support related EY Innovation initiatives, contributing to and leveraging a shared portfolio of agentic capabilities., • Integrate Data Agents with EY.ai Data Marketplace and the EY.ai Simulation Hub to support the broader AI Ready Data Strategy., • Manage adoption by managing demand, tracking usage, and measuring outcomes using clear KPIs., • Develop training content for the AI Ready Data Academy and cultivate a community of practice., • Communicate the value proposition of Data Agents to both internal and external audiences., • Support regional and service line data teams to promote adoption and identify high‑value use cases., • Design and delivery of technical integrations, including MCP server, enterprise data catalog, analytics tools, and Semantic Layer, knowledge graph platforms such as PoolParty (Graphwise), • Undergraduate degree, preferably in computer science, maths or engineering., • Master’s in Business Administration is a plus., • Demonstrable skills with AI and Agentic capabilities - fluent in all aspects of agentic tools, platforms and capabilities, • Proven experience across the data management lifecycle - including data quality, data modelling, data engineering etc, • Business acumen to translate client needs into actionable solutions., • Strong leadership and communication skills, with the ability to engage and influence stakeholders. At EY,we’lldevelop you with future-focused skills and equip you with world-class experiences.We’llempower you in a flexible environment, and fuel you and your extraordinary talents in a diverse and inclusive culture of globally connected teams. Learn more . EY is building a better working world by creating new value for clients, people, society and the planet, while building trust in capital markets. Enabled by data, AI and advanced technology, EY teams help clients shape the future with confidence and develop answers for the most pressing issues of today and tomorrow. EY teams work across a full spectrum of services in assurance, consulting, tax, strategy and transactions. Fueled by sector insights, a globally connected, multi-disciplinary network and diverse ecosystem partners, EY teams can provide services in more than 150 countries and territories. #J-18808-Ljbffr

Selection changes the language of the page/content London, England, United Kingdom Software and Services The Wallet & Payments Security Solutions team sits at the intersection of developer experience and customer trust, building the foundational security layer that every product in the Apple Pay portfolio depends on. We are a group of security engineers passionate about enabling fast, safe engineering at scale across a modern, Kubernetes-based multi-cloud platform. This role is an opportunity to shape secure-by-default practices across Apple Pay engineering organizations working on Payments, Transit, Access, & Identity products. If you're passionate about security and customer safety, we may have the job for you. As a Platform Security Engineer on the Wallet & Payments Security Solutions team, you will design, build, and operate security application frameworks and solutions for a Kubernetes-based developer platform spanning multiple cloud providers. You will partner closely with platform and product engineering teams to embed security into every stage of the development lifecycle, ensuring guardrails never become friction. Your work will directly protect Apple customers and the engineers who build the products they rely on every day. Further, as part of this role, you will frequently collaborate with other security engineers and architects across Apple to identify, define and design security solutions which elevate overall security profile of Apple Services. • Develop internal frameworks, libraries, tools and processes that make the secure path the easiest path for every engineer on the platform, • Design and implement security frameworks, controls, tooling, and automation for a Kubernetes-based multi-cloud platform serving Wallet & Payments Engineering, • Champion secure-by-default infrastructure patterns and drive adoption of safe engineering practices across the organization without sacrificing developer velocity, • Partner with platform, product, and infrastructure engineering teams to identify security risks and deliver pragmatic mitigations at the architectural level, • Conduct threat modeling of new platform capabilities to incorporate security during early phases of platform development, • Respond to and lead resolution of incidents affecting the security of developer platform, conducting thorough post-incident reviews, • Work AI-forward by using coding agents and LLM-based tooling as a normal part of development, and own the correctness of what you ship regardless of what drafted it., • Experience in platform security and/or software engineering experience in infrastructure and application development, or a closely related security engineering discipline, • Experience in Go, Kotlin/Java and Spring Framework., • Ability to communicate thoughtfully and clearly, both verbally and in writing, to discuss complex technical concepts with diverse audiences, including global teams., • Passion for developer enablement and building "security as a product", • The tenacity and perseverance to drive a complex project all the way from conception to production., • BS in Computer Science or equivalent experience/skills in application development and security., • Prior experience contributing to or driving a secure-by-default platform initiative across a large engineering organization, • Experience with Identity and Access management frameworks, • Deep expertise in Kubernetes security, including RBAC, admission control, pod security standards, network policy, and workload identity, • Experience designing and implementing security controls across at least two major cloud providers and not just defining policies., • Experience hardening containers and orchestration: image provenance, admission control, runtime and network policy, service mesh configuration, and clean isolation across micro services, • Experience with Supply Chain Security and optimizing Vulnerability management loop., • Identity protocols and applied cryptography in practice: OAuth2, OIDC, JWT, SAML, mutual TLS, PKI, encryption and signing primitives., • Fluency with coding agents and LLM-based development tooling, and judgment about when to trust their output. At Apple, we're not all the same. And that's our greatest strength. We draw on the differences in who we are, what we've experienced and how we think. Because to create products that serve everyone, we believe in including everyone. Therefore, we are committed to treating all applicants fairly and equally. As a registered Disability Confident employer, we will work with applicants to make any reasonable accommodations. Apple will consider for employment all qualified applicants with criminal backgrounds in a manner consistent with applicable law. At Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong. #J-18808-Ljbffr

Hims & Hers is the leading health and wellness platform, on a mission to help the world feel great through the power of better health. We are redefining healthcare by putting the customer first and delivering access to care that is affordable, accessible, and personal, from diagnosis to treatment to delivery. No two people are the same, so we provide access to personalized care designed for results. By normalizing health & wellness challenges and innovating on their solutions, we’re making better health outcomes easier to achieve. Hims & Hers is a public company, traded on the NYSE under the ticker symbol “HIMS.” To learn more about the brand and offerings, you can visit hims.com/about and hims.com/how-it-works . For information on the company’s outstanding benefits, culture, and its talent-first flexible/remote work approach, see below and visit www.hims.com/careers-professionals. As a Senior Data Scientist at Hims & Hers, you are a core driver of technical execution and innovation within our data organization. You take complex business challenges and translate them into robust, scalable data products and machine learning models. You will be trusted to operate with high autonomy, owning your projects from the initial exploratory analysis through to production deployment. In this role, you will work closely with Product, Engineering, and Business stakeholders to deliver solutions that optimize our operations, refine our marketing efforts, and enhance the customer experience. You will not only build powerful models but also help uphold the engineering rigor and standards of our data team. Build from Scratch: Thrive in a 0-to-1 environment. You are comfortable rolling up your sleeves to write complex SQL, engineer your own features, and deploy baseline models (heuristics or simple ML) quickly to prove value before iterating toward complex solutions. End-to-End Execution: Own the complete model lifecycle, from data extraction and feature engineering to deployment, A/B testing, and ongoing performance monitoring. Cross-Functional Collaboration: Partner closely with Engineering, Product, and Finance teams to define technical requirements and translate model outputs into clear, actionable business insights. Uphold Technical Standards: Write clean, modular, and production-ready code. Actively participate in peer code reviews and contribute to the team’s technical best practices. Drive Project Delivery: Navigate technical ambiguity within your domain, breaking down complex project requirements into manageable, executable milestones. Team Mentorship: Provide technical guidance and support to junior data scientists and analysts, helping them troubleshoot roadblocks and adopt best practices. 5+ years of applied experience in Data Science or ML Engineering, with a track record of delivering production-ready models that drive measurable business value. Technical Proficiency: Strong expertise in Python and SQL. Deep familiarity with the Python data stack (pandas, NumPy, scikit-learn) and standard ML frameworks (such as PyTorch, XGBoost, or LightGBM). Engineering Rigor: Proven ability to build for production. Experience working in cloud-based environments (AWS or GCP) and familiarity with CI/CD workflows, version control (Git), and ML Ops principles. Analytical Problem Solving: Strong ability to connect technical metrics to business outcomes. You know how to choose the right algorithm for the right problem rather than just the most complex one. Communication: Excellent ability to explain technical concepts, model limitations, and analytical findings to non-technical stakeholders. Education: BS, MS, or equivalent experience in a quantitative field (Data Science, Statistics, Economics, CS, Applied Math, etc.). 0-to-1 Execution: Experience taking the very first machine learning models in an organization from exploratory notebooks to reliable, automated production pipelines. Advanced Business ML (Experience in 1-2 of the following): Customer Behavior & Propensity Modeling: Building predictive models for churn, propensity-to-buy, lead scoring, or lifetime value (LTV) to directly drive targeted marketing and product interventions. Applied Forecasting: Time-series forecasting, anomaly detection, or handling non-stationary data for demand or revenue planning. Optimization: Building engines for marketing spend, inventory management, or resource allocation. Causal Inference: Designing robust experiments (e.g., quasi-experiments, difference-in-differences) to measure true business impact beyond standard A/B testing. We are committed to building a workforce that reflects diverse perspectives and prioritizes ethics, wellness, and a strong sense of belonging. Hims considers all qualified applicants for employment, including applicants with arrest or conviction records, in accordance with the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance, the California Fair Chance Act, and any similar state or local fair chance laws. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. Hims & Hers is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, please contact us at and describe the needed accommodation. Your privacy is important to us, and any information you share will only be used for the legitimate purpose of considering your request for accommodation. Hims & Hers gives consideration to all qualified applicants without regard to any protected status, including disability. Please do not send resumes to this email address. To learn more about how we collect, use, retain, and disclose Personal Information, please visit Global Candidate Privacy Statement. #J-18808-Ljbffr

Applied Intuition, Inc. is powering the future of physical AI. Founded in 2017 and now valued at $15 billion, the Silicon Valley company is creating the digital infrastructure needed to bring intelligence to every moving machine on the planet. Applied Intuition services the automotive, defense, trucking, construction, mining and agriculture industries in three core areas: tools and infrastructure, operating systems, and autonomy. Eighteen of the top 20 global automakers, as well as the United States military and its allies, trust the company’s solutions to deliver physical intelligence. Applied Intuition is headquartered in Sunnyvale, California, with offices in Washington, D.C.; San Diego; Ft. Walton Beach, Florida; Ann Arbor, Michigan; London; Stuttgart; Munich; Stockholm; Bangalore; Seoul; and Tokyo. Learn more at applied.co. We are an in-office company, and our expectation is that full-time employees primarily work from their Applied Intuition office 5 days a week. However, we also recognize the importance of flexibility and trust our employees to manage their schedules responsibly. This may include occasional remote work, starting the day with morning meetings from home before heading to the office, or leaving earlier when needed to accommodate family commitments. This in-office expectation does not apply to contractor positions Full-time /London (Engineering) Applied Intuition UK is a software and infrastructure supplier that accelerates the deployment of next-generation autonomous capabilities to the warfighter across air, land, sea, and space. A subsidiary of Applied Intuition, we deliver dual-use solutions to national security customers that build upon several years of product development and experience from commercial autonomy programs. Based in London, our seasoned defence team hails from Palantir, Anduril, SpaceX, Google, Lockheed Martin, and the UK and US Armed Services. Learn more at appliedintuitiondefense.com. As a senior software engineer on the UK engineering team, your day-to-day activities will vary. Somedays you might find yourself in the field, working alongside our forward deployment team integrating with customer platforms and technologies, other days you might be leading the design on a brand-new product to satisfy the requirements of various different customers and partners that we work with. Every day is different, and each day is exciting. You are given the opportunity to showcase the skills you’ve learned during your career, and teach the more junior members of the team. You will build, test and deploy your software and watch it actually be used. • Lead the design, development, and optimization of new tools and products, taking them through from incubation all the way to production, • Spot the ineffectiveness of the processes and code you work with daily to ensure the team are always working to the best of their abilities, • Integrate software from customers and other teams into the products we are making, • Write, test, and debug efficient modern C++ code for complex software solutions with the help of AI tooling, • Work closely with product managers and customers to understand requirements and translate them into technical solutions, • Train and mentor junior engineers as we grow the UK team, fostering a culture of learning and improvement, • Build awesome software that you are proud of, • Bachelor’s degree in computer science/related engineering field, • 5+ years of hands-on experience developing performant modern C++, or high willingness to learn C++ which is our primary programming language for all development, • Strong procedural and object-oriented programming experience that employs clean code principles and good OOP design patterns/principles, • Experience developing in Docker and containerized development environments, and using Linux-based operating systems, • General willingness to travel for company business between our offices, as well as to customer sites, • Must have ability to hold UK Security Clearance (current or previous preferred), • 7+ years of experience developing software in modern C++ and Python, • Experience working on distributed systems, with simulation technology and autonomy, • Experience with Bazel, Nix and other similar technologies, • Experience deploying to, and working with infrastructure technologies, • Experience working projects related to national security for one or more government agencies, • References who will describe them as low-ego, highly motivated, thoughtfully opinionated, strong communicators and curious listeners Don’t meet every single requirement? If you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyway. You may be just the right candidate for this or other roles. Applied Intuition is an equal opportunity employer and federal contractor or subcontractor. Consequently, the parties agree that, as applicable, they will abide by the requirements of 41 CFR 60-1.4(a), 41 CFR 60-300.5(a) and 41 CFR 60-741.5(a) and that these laws are incorporated herein by reference. These regulations prohibit discrimination against qualified individuals based on their status as protected veterans or individuals with disabilities, and prohibit discrimination against all individuals based on their race, color, religion, sex, sexual orientation, gender identity or national origin. These regulations require that covered prime contractors and subcontractors take affirmative action to employ and advance in employment individuals without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status or disability. The parties also agree that, as applicable, they will abide by the requirements of Executive Order 13496 (29 CFR Part 471, Appendix A to Subpart A), relating to the notice of employee rights under federal labor laws. Applied Intuition is committed to providing an accessible and inclusive application and interview experience to applicants who are disabled veterans and other applicants with disabilities or medical conditions. Reasonable accommodations are available, requesting an accommodation will not affect your candidacy in any way, and you are not required to disclose the nature of your disability or medical condition in order to make a request. If you require an accommodation please contact . We will work with you! #J-18808-Ljbffr

Salary: £63,000 - 103,000 per year • Bachelors degree or experience in a professional field or military, • Experience as a technical specialist in design and architecture, • Experience with databases such as SQL, NoSQL, Hadoop, Spark, Kafka, or Kinesis, • Experience consulting on, designing, and implementing serverless distributed solutions, • Software development experience with an object-oriented language, • Experience with cloud-based solutions (AWS or equivalent), systems, networks, and operating systems, • Experience with external- or internal-customer-facing, complex, large-scale project management, • Experience building complex, highly scalable systems involving predictive models or machine learning applications, • Experience in data and machine learning engineering and cloud-native technologies, • Eligibility to obtain and maintain UK Government Security Clearance, • Preferred: Masters degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science, or a PhD, • Preferred: Knowledge of AWS services such as EC2, ELB, RDS, VPC, Route 53, and S3, • Preferred: Experience with the software development life cycle and agile or iterative methodologies, • Preferred: Experience facilitating discussions with senior leadership about technical and architectural trade-offs, best practices, and risk mitigation, • Preferred: Experience creating and delivering written and oral communications for technical and non-technical audiences, • Preferred: Python experience and hands-on experience building models with deep learning frameworks such as TensorFlow, Keras, PyTorch, or MXNet, • Lead complex AI/ML engagements from strategic planning through pre-production deployment and optimisation, • Architect and implement advanced solutions using AWS AI/ML services, particularly generative AI with Amazon Bedrock and SageMaker, • Provide technical leadership and mentor junior consultants while promoting best practices across delivery teams, • Partner with customers to translate business challenges into measurable machine learning outcomes and delivery roadmaps, • Drive applied AI/ML innovation and contribute methodologies and reusable solutions across our practice, • Influence customer AI strategy with technical expertise and industry insights, • Lead multidisciplinary teams and coordinate stakeholders to deliver high-impact AI solutions, • Provide thought leadership in internal and external engagements, • Support presales activities by providing technical expertise and reviewing project scope and risks, • AI, • AWS, • Architect, • Cloud, • EC2, • Hadoop, • Support, • Kafka, • Keras, • Machine Learning, • NoSQL, • PyTorch, • Python, • SQL, • Security, • Serverless, • Spark, • TensorFlow, • Network, • Web As a Senior AI/ML Consultant in AWS Professional Services, you will lead delivery of advanced AI and machine learning solutions for enterprise customers, shape technical strategy, and advise customers through their AI transformation. The role is based at our AWS offices in London, Manchester, Bristol, or Cambridge when you are not at a customer site. We are AWS, a comprehensive and widely adopted cloud platform, and we value diverse experiences, inclusion, mentorship, career development, and work-life harmony. Our employee-led affinity groups, learning opportunities, and knowledge-sharing resources support our peoples growth. We are an equal opportunity employer and can provide workplace accommodations during the application and hiring process. #J-18808-Ljbffr

We established Faculty in 2014 because we thought that AI would be the most important technology of our time. Since then, we’ve worked with over 350 global customers to transform their performance through human-centric AI. You can read about our real-world impact here. We don’t chase hype cycles. We innovate, build and deploy responsible AI which moves the needle - and we know a thing or two about doing it well. We bring an unparalleled depth of technical, product and delivery expertise to our clients who span government, finance, retail, energy, life sciences and defence. Our business, and reputation, is growing fast and we’re always on the lookout for individuals who share our intellectual curiosity and desire to build a positive legacy through technology. AI is an epoch-defining technology, join a company where you’ll be empowered to envision its most powerful applications, and to make them happen. As a Software Engineer in the AI Platform team, you will be the architect of the infrastructure that makes world-class AI possible. Working closely with the Applied AI team, you’ll be building and maintaining the data science, MLOps, and deployment tooling that empowers our team of over 100 Data Scientists and Engineers. You will take ownership of the platform that enables us to transition from complex exploration to full-stack, production-grade machine learning products, ensuring our solutions are high-performing, scalable, and seamlessly integrated into diverse client environments. Taking ownership of our existing deployment and MLOps tooling to ensure our software delivery remains a significant lever for quality and reliability. Contributing to the continuous evolution of our technology stack, from building new features in our notebook development environments to refining model monitoring systems. Collaborating with a small, fast-moving team of customer-facing technologists to design and build the infrastructure our delivery teams need to succeed. Designing and implementing infrastructure-as-code and DevSecOps processes to support distributed, containerised microservices architectures. Integrating our core platform services across multiple cloud environments, including AWS, Azure, and GCP, to provide flexible solutions for our global clients. Scaling our internal enablement capabilities, acting as an entrepreneurial force that removes technical friction and accelerates the deployment of machine learning. You are a Software Engineer who is passionate about building internal tools and takes pride in creating the foundational systems that enable others to excel. You understand the nuances of the machine learning product lifecycle and have a clear vision for how to move models efficiently from exploration to production. You possess modern systems programming skills in Python or Go, and you are comfortable selecting the best‑fit technology for complex infrastructure challenges. You bring practical experience with containerisation and orchestration, specifically using Docker and Kubernetes to manage distributed systems at scale. You have a strong background in Infrastructure-as-Code (IaaC) using tools like Terraform or CloudFormation, combined with a deep interest in DevSecOps practices. You thrive in small, ambitious teams where you can take high levels of ownership and communicate effectively with both technical and non-technical peers. Talent Team Screen (30 minutes) Pair Programming Interview (90 minutes) System Design Interview (90 minutes) Commercial Interview (60 minutes) We aim to grow the best team - not the most similar one. We know that diversity of individuals foster diversity of thought, and that strengthens our principle of seeking truth. And we know from experience that diverse teams deliver better work, relevant to the world in which we live. We’re united by a deep intellectual curiosity and desire to use our abilities for measurable positive impact. We strongly encourage applications from people of all backgrounds, ethnicities, genders, religions and sexual orientations. If you don’t feel you meet all the requirements, but are excited by the role and know you bring some key strengths, please don't hesitate in applying as you might be right for this role, or other roles. We are open to conversations about part‑time hours. A note on AI: we're happy for you to use it for research and interview prep, but please don't use it to generate answers during live interviews. We also use an AI note-taker (Metaview) in interviews so interviewers can stay present (which you can opt out of just let us know,) and every application is reviewed by a human, never decided by AI. #J-18808-Ljbffr

Anthropic's mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. We're looking for an Associate to join our Applied AI team in a rotational program designed to develop the next generation of technical leaders in AI. This role combines deep technical work with customer engagement, positioning you to transition into SA, Product Engineering, or other Applied AI functions after the program. Over 6 months, you'll work across a variety of Applied AI segments and functions, gaining exposure to enterprise sales cycles, product development, and technical architecture while building solutions that directly impact how our customers deploy Claude. As an Associate, you'll be a technical builder first: developing agents, creating Skills, designing internal assets, and working hands-on with Claude's SDK and API. You'll collaborate closely with Solutions Architects, Product Engineers, and Forward Deployed Engineers on complex customer problems while also partnering with Account Executives to support sales cycles. • Build production-ready agents, Skills, and solutions using Claude's SDK and API, • Develop scalable internal and customer-facing technical assets (code examples, architectures, integration patterns), • Document and share best practices for LLM prompting, evaluation, agentic workflows, and architecture design, • Create demo environments and technical proof-of-concepts that showcase Claude's capabilities, • Conduct technical discovery calls to understand customer requirements and development workflows, • Help customers design scalable architectures and develop evaluation frameworks for their AI implementations, • Provide technical troubleshooting and implementation support during customer evaluations, • Work alongside Solutions Architects and Product Engineers on complex technical requirements in sales cycles, • Partner with Forward Deployed Engineers on post-deployment optimization and expansion opportunities, • Synthesize technical feedback from customer interactions to inform product roadmap, • Rotate through different Applied AI segments over the 6-month program, gaining exposure to various customer profiles and use cases, • 0-2 years of software engineering, technical consulting, or solutions architecture experience, • Strong coding fundamentals with experience in Python, TypeScript/JavaScript, or similar languages, • Demonstrated ability to build functional applications, tools, or technical projects, • Experience with APIs, SDKs, and integration patterns, • Understanding of software development workflows, architecture patterns, and developer productivity tools, • 0-2 years of customer-facing technical experience (sales engineering, technical support, consulting, teaching, or similar), • Comfort presenting technical concepts and adapting communication style for different audiences, • Strong problem-solving skills with ability to debug issues and troubleshoot technical challenges, • Self-starter mentality with bias toward action: you see problems and build solutions without waiting for direction, • Genuine enthusiasm for AI technology and eagerness to learn in a fast-paced environment, • Growth mindset with ability to take ownership of projects and drive them to completion, • Fluency in more than one language Deadline to apply: None. Applications will be reviewed on a rolling basis. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: £115,000 - £115,000 GBP Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact - advancing our long-term goals of steerable, trustworthy AI - rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process. #J-18808-Ljbffr