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Company Description FourPlus Immersive specializes in developing cutting-edge software solutions that combine XR (extended reality) and AI. Their flagship product, Eclipse Creator, supports the life sciences sector through skills training, process workflow mapping, and recruitment tools for healthcare professionals and pharmaceutical manufacturers. Leveraging expertise in immersive technology, FourPlus addresses challenges posed by advanced therapies, propelling the modernization of medicine production. With a focus on transforming business practices and accelerating the delivery of revolutionary treatments, FourPlus is a key contributor to the advancements of Industry 4.0 in life sciences. What you'll work on • Extracting and structuring data from XR simulations (Unity/Unreal), • Turning human behaviour into usable datasets, • Building multimodal models (interaction data + video + SOPs), • Developing systems like deviation detection, performance scoring, and AI feedback This role is for you if • You’ve built ML systems end-to-end (not just models), • You’re comfortable working with messy, real-world data, • You like defining structure where none exists, • You want to work on something hard, applied, and high-impact This is not • A pure research role, • A “train models on clean datasets” job, • A backend-only position Stack (flexible) Python, PyTorch, CV/vision models, LLMs, XR data (Unreal) If you are based in the UK and think you align with the above spec please get in touch: ivan@fourplus.co.uk

Do you want to productionise end-to-end enterprise GenAI systems? Have you built scalable ML platforms and MLOps infrastructure in production? Are you ready to establish ML Engineering capability inside a business heavily investing in AI? A large UK professional services organisation is building out its ML Engineering capability and hiring a Lead Machine Learning Engineer to help shape the function from the ground up. This is a hands-on role focused on production AI systems, MLOps, cloud ML infrastructure, and enterprise GenAI deployment. Current projects include large-scale document AI workflows using LLMs to process and structure complex documents. Key responsibilities: • Productionise LLM and GenAI systems, • Build scalable MLOps and deployment pipelines, • Develop AI infrastructure in Azure and Databricks, • Create data pipelines for enterprise AI workflows, • Work closely with DS teams and business stakeholders Key details: • £90k + ~10% bonus, • Essentially remote across the UK, • 35-hour week with flexible hours, • Stack: Azure ML, AI Foundry, Databricks, Python, FastAPI, • 12-month FTC with strong chance of permanent conversion, • Cannot sponsor Requirements: • 7+ years across MLE/MLOps/Data Engineering/SWE, • Production ML deployment experience, • LLM/NLP/GenAI exposure, • Strong stakeholder management and independent delivery skills Interested? Please apply below.

Contract AI Engineer | Outside IR35 | Agentic AI / LLMs / RAG Conquer AI is hiring a Contract AI Engineer We’re looking for a highly capable, hands-on AI Engineer with a strong traditional software engineering background and deep applied AI experience. This is an Outside IR35 contract working on greenfield AI projects for enterprise clients. You’ll be helping design and build real-world systems using LLMs, RAG, vector databases, agentic AI, and workflow automation. This is not a research-only role. We need someone who can build production-grade systems, integrate with existing platforms, and move quickly from problem definition to working software. What you’ll be working on: Agentic AI workflow automation LLM-powered applications RAG and knowledge systems Vector database architecture and retrieval pipelines Document intelligence and information extraction AI systems that connect into business workflows API integrations and backend services Greenfield client projects and internal Conquer AI product work Core skills we’re looking for: Strong machine learning experience Strong traditional software engineering background Python Node.js TypeScript LLMs RAG Vector databases Agentic AI systems Workflow automation API integrations Backend engineering You’ll be a strong fit if you: Have built real AI systems beyond prototypes Can design and ship reliable backend services Understand retrieval, ranking, chunking, embeddings, and evaluation Have experience integrating LLMs into business workflows Can work with ambiguity and move quickly Are comfortable working with client-facing teams Can turn vague business problems into working technical solutions Care about practical delivery, not just experimentation Nice to have: Experience with AWS, Azure, or GCP Experience with LangChain, LlamaIndex, Semantic Kernel, CrewAI, AutoGen, or similar Experience with Pinecone, Weaviate, Qdrant, Chroma, pgvector, or similar Experience with document processing, OCR, structured extraction, or enterprise search Experience in consulting, enterprise delivery, SaaS, or startup environments About Conquer AI Conquer AI builds bespoke agentic AI systems for enterprise clients. We work with clients to understand their workflows, identify where AI can automate or augment work, and build practical systems that operate inside their existing environment. Our work spans document intelligence, workflow automation, knowledge retrieval, operational copilots, AI agents, data extraction, and enterprise integrations. Contract: Outside IR35 Location: UK-based preferred Working style: Hybrid / remote, with occasional client or team sessions Start: ASAP Engagement: Contract If you’re a strong software engineer with serious applied AI experience and you want to work on meaningful agentic AI systems, we’d like to speak with you.

Software Engineer (backend) 📍Location: UK (Remote) 💰Salary: £125k –£145k + annual performance bonus ❌No visa sponsorship offered Capital markets move trillions. The legal documents underpinning those transactions are dense, nuanced, and mission-critical, and right now, most of that complexity is still handled by hand. This company is changing that. Built on years of machine learning PhD expertise, backed by a top-tier venture firm, and now operating at global scale following a high-profile acquisition, this team is tackling some of the hardest NLP problems in finance and law. Their customers include many of the world's leading law firms and the demand for what they're building is accelerating fast. As a Software Engineer, you won't be maintaining someone else's roadmap. You'll be architecting the critical backbone between a cutting-edge AI data platform and the professionals who depend on it daily. Your decisions will ship. Your influence will stick. If you want to do the most meaningful work of your career, in a team that moves fast, thinks deeply, and gives a damn about craft - read on. The Role • Design and build scalable backend services and APIs that power a document analysis platform used by major legal and financial institutions, • Write high-performance, maintainable server-side code and data processing pipelines, • Define clear, efficient API contracts and contribute meaningfully to service architecture decisions, • Design compositional API primitives that accelerate the productionisation of a growing library of document insights, • Build and maintain integrations with third-party services and internal ML systems, • Contribute to frontend features and components as needed to deliver end-to-end functionality, • Drive performance optimisation for data-intensive backend operations, • Champion engineering excellence — contribute to code practices, design patterns, and long-term maintainability, • Improve developer experience by automating and improving CI/CD and day-to-day production operations Skills Needed Required: • 6+ years of professional full-stack development experience with a strong backend focus, • Proficiency in backend technologies - Python (FastAPI, Django, or Flask) is preferred; Node.js, Java, or Go also considered, • Strong understanding of RESTful APIs, database design, and data modelling (SQL and NoSQL), • Experience with containerisation and orchestration (Docker, Kubernetes) and cloud platforms (AWS preferred), • Proficiency in TypeScript and React for frontend contributions, • Foundation in distributed systems, event-driven architectures, and web fundamentals, • Strong communication skills and a self-starting, action-biased approach to problem-solving, • Bachelor's degree in Computer Science or related field, or equivalent practical experience Preferred: • Experience with microservices architecture and message queues, • Experience building data processing pipelines or working with large-scale data systems, • Familiarity with CI/CD best practices and single-tenant architectures, • Experience optimising backend performance for data-intensive applications, • Mentorship experience and a track record of ownership in previous roles, • Interest in language, economics, or legal/financial domains Benefits • 15 - 20% annual performance bonus, • Fully remote - work from anywhere in the UK, • Private medical, dental, and vision insurance, • Pension and retirement planning support, • Health and wellbeing reimbursement (including fitness and mindfulness), • Flexible paid time off Research indicates that men will apply to a role when they only meet 50-60% of the descriptions, however, when looking at women and other minority groups, they can look for up to a 99% match in order to apply to a role. If you feel you are a fit for our role, please still apply, don’t worry if you don’t tick every single box. We’d still love to hear from you. We encourage underrepresented talent to apply to all our roles & support accessibility needs

Senior AI Engineer (NLP / LLMs) – remote (UK based) £70-100k depending on experience A high-growth SaaS company is hiring a Senior AI Engineer to help build intelligent, mission-critical systems used in highly regulated environments. The platform applies machine learning and large language models across complex, end-to-end data workflows, solving real-world problems with measurable social impact. The Role As a Senior AI Engineer, you’ll design, build and deploy advanced NLP and LLM-based solutions, taking models from research through to production. You’ll work closely with AI, data, MLOps and product teams to translate business and regulatory requirements into scalable, reliable AI systems. This is a hands-on role for someone who enjoys owning outcomes, balancing experimentation with real-world delivery. What You’ll Be Doing • Designing and developing NLP and LLM-driven solutions for complex, real-world use cases, • Fine-tuning and adapting foundation models using domain-specific data, • Building evaluation frameworks, prompt testing tools and data preprocessing pipelines, • Monitoring, optimising and maintaining deployed models for performance, cost and reliability, • Implementing explainability, fairness and bias-mitigation strategies, • Collaborating on MLOps pipelines, CI/CD workflows and production deployments, • Mentoring junior engineers and promoting best practices across the team, • Staying current with advances in AI, NLP and MLOps to drive continuous improvement What We’re Looking For • Proven experience as an AI or Machine Learning Engineer with end-to-end model ownership, • Strong expertise in NLP and LLMs (transformers, fine-tuning, RAG, agents), • Experience translating research and experimentation into production systems, • Solid understanding of MLOps, including CI/CD, monitoring and model lifecycle management, • Hands-on experience with Docker and Kubernetes, • Strong communication skills and experience mentoring or leading others Nice to Have • Experience working in regulated or sensitive domains, • Exposure to graph-based retrieval techniques, • Experience with Azure ML and DevOps integrations

About Inworld Inworld is a product-oriented research lab of top AI researchers and engineers, developing best-in-class realtime multimodal models and the only realtime orchestration platform optimized for thousands of queries per second. We’ve raised more than $125M from Lightspeed, Section 32, Kleiner Perkins, Microsoft’s M12 venture fund, Founders Fund, Meta and Stanford, among others. Our technology has powered experiences from companies such as NVIDIA, Microsoft Xbox, Niantic, Logitech Streamlabs, Wishroll, Little Umbrella and Bible Chat. We’ve also been recognized by CB Insights as one of the 100 most promising AI companies globally and have been named one of LinkedIn's Top 10 Startups in the USA. Who We're Looking For A year ago, reliably working agentic systems and sub-second multimodal inference at scale barely existed. Nobody has a decade of experience here. So we're not screening for a resume template — we're looking for strong people from varied backgrounds who learn fast, thrive in ambiguity, and can show us what they've built, broken, and understood. Experience We Find Useful You don't need all of this. But you need enough to make a case. • Inference Optimization. Deep understanding of modern serving frameworks and techniques like vLLM or TRT-LLM., • Model Acceleration. Hands-on experience with quantization, distillation, caching strategies , continuous batching, paged attention, and speculative decoding., • High-Performance Systems. Proficiency in C++, CUDA, Rust, or highly optimized Python. You know how to profile code and squeeze every ounce of performance out of NVIDIA GPUs., • Distributed Systems & Scaling. Experience with Kubernetes, Ray, custom load balancing, multi-GPU/multi-node inference, and reliably handling thousands of concurrent connections., • Public work. Non-trivial systems programming projects, open-source contributions to major inference engines, or deep-dive technical write-ups., • Full-cycle ownership. You can take a model from the research team, containerize it, optimize its serving, and ensure it runs reliably in production., • Background. PhD in CS, Physics, Math, or equivalent practical experience building backend or ML systems. Who Thrives Here • You don’t need a roadmap to start walking; you’re comfortable picking a direction and building the map as you go., • You believe engineering isn't finished until it’s shipped and stable. You have a bias for impact over purely theoretical optimizations., • You don't just ship code; you obsess over the why. You’re the first to question an architecture if you think there’s a better way to solve the core latency or throughput problem., • You aren't satisfied with "the PM said so." You thrive on deep context and want to understand the fundamental logic behind every decision we make. What Working Here Is Like We hand you unclear problems and expect you to make them clear. We value engineers who say "I don't know yet" and then design the benchmark or prototype that finds out. We treat performance, latency, and reliability as first-class product features, not a box to check before launch. Impact comes before everything else, though we support sharing work and open-source contributions that move the field forward. Your work should be visible. Flat structure, fast iterations, minimal process theater. The base salary range for this full-time position is £140,000 – £200,000. In addition to base pay, total compensation includes equity and benefits. Within the range, individual pay is determined by work location, level, and additional factors, including competencies, experience, and business needs. The base pay range is subject to change and may be modified in the future. Candidates must already have the legal right to work in the United Kingdom, as visa sponsorship is not available for this role. For candidates interested in relocating to the San Francisco Bay Area in the future, full U.S. visa and relocation support may be available, subject to business needs and applicable legal and work authorization requirements.

Lead Machine Learning Engineer 12 Month FTC Remote UK, up to £90,000, 12 month fixed term contract This is a rare opportunity to take ownership of machine learning delivery in a business that is actively investing in AI and moving from proof of concept into production. You will play a pivotal role in shaping how advanced ML and generative AI solutions are engineered, deployed and scaled, with genuine scope for the role to become permanent. The Company They are a large, well established UK organisation operating in a highly regulated, information rich environment. With thousands of colleagues nationwide, they combine deep domain expertise with a strong focus on people, quality and long term outcomes. Data and AI are now a strategic priority, with senior backing to build robust, production grade ML capability. The Role • Lead the engineering and productionisation of machine learning and generative AI solutions., • Build and operate end to end ML pipelines, including data preparation, model deployment, monitoring and governance., • Work closely with data scientists and data engineers to turn experiments and POCs into scalable, reliable services., • Develop solutions for large scale unstructured data, including complex document processing and LLM ready data pipelines., • Own MLOps practices, covering CI/CD, model serving, observability and lifecycle management., • Provide hands on technical leadership, contributing to architecture decisions and best practice., • Act as a delivery focused partner to stakeholders, confidently explaining trade offs and recommendations. Your Skills & Experience • Strong commercial experience as an ML Engineer or MLOps focused engineer, ideally with a software engineering background., • Proven ability to deploy, operate and maintain machine learning systems in production., • Hands on experience with cloud based data and ML platforms, particularly on Azure., • Solid knowledge of Databricks and modern data engineering concepts such as lakehouse architectures., • Experience preparing data and pipelines for LLM based use cases and NLP workloads., • Strong Python skills, with experience building APIs or services, for example using FastAPI., • Confidence working across the full delivery lifecycle, from design through to monitoring and optimisation., • Clear communication skills and comfort working directly with non technical stakeholders. What They Offer • Excellent work life balance and a supportive, collaborative culture., • The chance to shape ML engineering standards and capability from the ground up., • Strong potential for the role to become permanent, with future people leadership opportunities. How to Apply If you are an experienced ML Engineer looking for a hands on role with real influence and long term potential, apply now to find out more.

Machine Learning Engineer (NLP) Location: remote only within the UK Salary: up to £100,000 Job Purpose As a Machine Learning Engineer (NLP), you will work with our small but growing team and play an active role in building our Machine Learning/NLP capability. You will be responsible for developing and refining the NLP algorithms and infrastructure of our AI-powered design platform. You will apply SOTA NLP techniques to solve complex problems while collaborating with cross-functional teams. As Machine Learning Engineer (NLP), you will be responsible for: • Building and deploying NLP models using the latest techniques to solve real business problems at scale, and exposing them through APIs, • Working with unstructured data to extract insights and build robust data pipelines, • Evaluating, tracking, and improving the performance of NLP models through MLOps, • Driving innovation through research, experimentation, and rapid prototyping of MVPs and POCs, collaborating with engineers and product teams to validate findings and plan execution, • Communicating technical concepts and results to non-technical stakeholders, • Playing an active role in the wider team and growth of the business To be successful in this role you will have: • Building and deploying NLP models using the latest techniques to solve real business problems at scale, and exposing them through APIs, • Working with unstructured data to extract insights and build robust data pipelines, • valuating, tracking, and improving the performance of NLP models through MLOps, • Driving innovation through research, experimentation, and rapid prototyping of MVPs and POCs, collaborating with engineers and product teams to validate findings and plan execution, • Communicating technical concepts and results to non-technical stakeholders, • Playing an active role in the wider team and growth of the business, and building scalable systems, • Have experience working with Azure, AWS or GCP, • Be a relentless problem solver, understanding requirements and designing solutions, • An entrepreneurial spirit and an interest in building world-changing ethical AI solutions, • Excellent communication skills and be able to explain complex technical concepts to non-technical stakeholders, • Be detail-oriented and able to manage multiple projects simultaneously Start-up life is not for everyone! To really thrive with us you will be 'Start-up ready'. You are naturally proactive, open to change, have a continuous improvement mindset, are flexible, happy to go beyond your brief, enjoy working at pace and are comfortable with ambiguity. And finally, you will really resonate with our values: • Customer Focus - we are obsessive about delivering value and reducing complexity for customers, • Collaboration: we’re all about the team - collaborating, supporting and recognising everyone’s contributions, • Openness & Honesty: we are open, honest, and straight-talking with each other and our customers, • Authenticity & Humility: we bring our whole selves to work, and we have the humility and self-honesty to admit when we are wrong

Job Title: Data Scientist/Machine Learning Engineer Location: UK Experience: 2–5 years Education: Master's in Science (IT/Computer Science/Engineer) Employment Type: Full-Time UK based candidates only. Information Tech Consultants Ltd (ITC) is an IT management and consulting firm based in Central London. Information Tech Consultants Ltd (ITC) is an IT management and consulting firm based in Central London. We are responsible for sourcing and hiring field experts for various companies. We primarily work with Software and Cloud Hosted Services organizations as well as Mobile Apps and Service companies. Required Skills: • 2-4 years of experience in Data science/Machine learning models from coding to deployment., • Work with datasets using Python or R, SQL, No SQL., • Assist in developing predictive and statistical models, • Write and optimize queries using SQL., • Familiarity with data manipulation libraries (Pandas, NumPy), Understanding of statistics and probability., • Hands-on experience with ML libraries like Scikit-learn, TensorFlow, or PyTorch. Preferred Skills: • Hands on experience in coding (mandatory python and SQL or C++)., • Understanding of Generative AI, Computer Vision cloud technology, NLP, Deep Learning., • Familiarity working with large data sets., • Project Management background preferred. Qualifications : • Master’s (Required) in Data Science, Mathematics, Statistics, Economics, IT related fields and 2- 4 years of experience in Information Technology., • You should be entitled to work in the UK with legal work authorization status., • Must be willing to travel within the UK as per project/client requirements., • Excellent communication skills and teamwork skills.

👋 About Renude Renude builds AI-powered software for the beauty industry, helping brands deliver personalised, expertise-focused customer support through intelligent digital agents. Our technology powers e-commerce experiences including: skin analysis, product recommendation and LLM-based chat. We’ve been awarded by CEW, Beauty Innovation Awards, Tech Nation and more. We have raised over $4M from leading tech investors in addition to being awarded Innovate UK Grants. Our team combines tech, formulation, dermatology, e-commerce and sales expertise. 🔧 What You'll Do We’re hiring a mid-senior (4+ years experience) AI Engineer to help design, build, and scale our production AI systems with ownership from design to deployment. You’ll work end-to-end across Agentic RAG conversational agents, Agent orchestration, fine-tuning models, retrieval pipelines, evaluation frameworks and generating product recommendation for real customer interactions to deliver reliable AI-powered experiences in production. • Design, build, and deploy Agentic AI workflows and RAG-powered applications for real-world use cases, • Develop scalable backend services and APIs powering AI agents and conversational systems, • Build and optimise retrieval pipelines including embeddings, chunking, reranking, memory and vector search, • Collaborate closely with product, design, and engineering teams to shape AI-first experiences, • Integrate LLM systems into user-facing web applications and product features, • Improve response quality, reliability, latency, observability and cost efficiency of production AI systems, • Evaluate new AI frameworks, tools, and orchestration approaches across the rapidly evolving LLM ecosystem, • Influence architecture decisions for scalable, secure, and production-ready AI infrastructure ✅ What We're Looking For Must-Haves: • Bachelor’s degree in Computer Science, Artificial Intelligence, Engineering, or equivalent practical experience, • 4+ years experience building and deploying production AI applications, • 2+ years experience developing LLM-powered products, conversational AI, RAG systems, or agentic workflows, • Strong Python skills and experience building backend systems and APIs, • Hands on experience building agentic workflows, tool-calling pipelines, and stateful orchestration using frameworks such as LangGraph, LangChain, LlamaIndex, AutoGen, CrewAI or similar agent orchestration frameworks, • Strong experience designing and optimising retrieval systems, including vector stores (Pinecone, Weaviate, Chroma), graph-based RAG architectures, hybrid retrieval, reranking, and semantic search pipelines, • Experience with production optimisation for RAG systems, including latency optimisation, token cost control, context management, monitoring, guardrails and prompt versioning, • Exposure to AIOps/MLOps practices and hands-on experience with AWS Bedrock, SageMaker, Vertex AI, or similar cloud AI platforms, • Comfortable working autonomously and taking ownership in a fast-moving, remote, startup environment Nice-to-Haves: • Masters or advanced degree in artificial intelligence, machine learning, natural language processing or related field, • Experience with LLM fine-tuning techniques such as LoRA, QLoRA, supervised fine-tuning (SFT), instruction tuning, and parameter-efficient model adaptation workflows, • Experience with evaluation and monitoring frameworks for LLM systems, including RAGAS, OpenEvals, DeepEval, LangSmith, OpenTelemetry or LLM-as-a-Judge evaluation frameworks, • Familiarity with graph databases such as Neo4j or Amazon Neptune, • Experience with recommendation systems, personalisation pipelines or ranking systems, • Experience building modern web applications using Django, FastAPI, React, or similar frameworks, • Comfortable using Docker and containerised development workflows, • Exposure to CI/CD pipelines, infrastructure-as-code, and cloud-native deployment practices 🌱 What We Offer • Competitive compensation (based on experience), • Remote-friendly culture with flexible working hours, • Opportunity to work with cutting edge technologies, • High ownership and real technical influence, • A supportive team that values product excellence and personal growth

Information about the Organization: Eruditus and its sister company Emeritus provide Private Online Courses (SPOCs) to students all over the world. We have partnered with top schools across the globe, such as Columbia Business School, The Tuck School of Business at Dartmouth, MIT, Wharton, London Business School, Cambridge, and UC Berkeley Haas School of Business, to provide condensed, intense, practical, and convenient programs, which can either be conducted completely or partially online. EMERITUS enables working professionals who cannot enroll into full-time courses to access a top-tier, affordable education that will give them the skills needed to be the business leaders of tomorrow. The Emeritus and Eruditus global team include 1,000+ employees located in the US, Dubai, Mexico, India, China, and Singapore. Information about the Learning Facilitator role: Emeritus is seeking a Program Facilitator in RAG and Context Engineering: Designing and Building Production-Grade AI Systems for MIT xPRO. The Program Facilitator should function as both: a technical subject matter expert (SME), and a learning support partner capable of helping learners apply complex concepts in practice, through the 8-week online program. The facilitator must have industry experience and demonstrated knowledge of the course subject area; They will guide learners through complex topics, requiring significantly more than general familiarity with AI tools. The Facilitator should have hands-on experience building or working with retrieval-aware AI systems and enough practical depth to support live labs, troubleshoot learner challenges, and guide architectural reasoning throughout the program This is a great role for someone who wants work flexibility and the chance to diversify their resume with consultancy and teaching experience. This is an independent contractor position in a remote setting. Key Responsibilities of the Program Facilitator include but are not limited to: • Facilitate weekly office hours and moderate required discussion boards., • Facilitate lab sessions weekly., • Moderate and guide learner engagement during faculty live sessions., • Support learners in synthesizing live session content delivered by the faculty (e.g., AI tools in cybercrime, GRC frameworks, deepfake detection)., • Assist with capstone assignment challenges., • Collaborate with academic delivery managers to improve engagement and comprehension., • Monitor learner progress and provide support or escalation as needed. Qualifications for the role: • 10+ years of extensive work experience as an Applied AI Consultant, Solutions Architect, Developer Educator, Technical Product Manager, Search/Retrieval Engineer or AI/ML Bootcamp Instructor., • A bachelor’s degree is required; plus, a master’s degree is preferred in one of the following fields: engineering, artificial intelligence, machine learning or any related fields., • Hands-on experience building or experimenting with Retrieval-Augmented Generation (RAG) systems., • Experience working with LLM APIs (e.g., OpenAI, Anthropic, OpenRouter, Gemini)., • Experience implementing or testing AI-powered applications., • Familiarity with vector databases, embeddings, semantic search, and retrieval workflows., • Experience evaluating LLM outputs and diagnosing system failures., • Experience supporting technical learners in applied or project-based environments., • Solid experience with Large Language Models (LLMs) how they work conceptually, limitations, prompt engineering strategies, context windows and tokenization and trade-offs across different model providers., • Solid experience with Retrieval-Augmented Generation (RAG), RAG architecture, retrieval pipelines, chunking strategies, embeddings, vector search, hybrid retrieval, reranking and retrieval quality trade-offs., • Solid experience with Evaluation and System Diagnosis, evaluation frameworks, benchmarking approaches, qualitative and quantitative evaluation, retrieval metrics, output quality assessment, failure analysis, and iterative system improvement., • Solid experience with Agentic and Tool-Based Systems, AI agents, orchestration concepts, tool calling, memory systems, retrieval-aware agents, and multi-step workflows., • Strong knowledge with APIs and Technical Workflow Support, API-based workflows, Python notebooks/scripts, environment setup, debugging common technical issues, JSON structures, and reading technical documentation., • Experience supporting executive or mid-career professionals in continuing education is highly preferred., • Excellent communication, facilitation and interpersonal skills with an ability to listen effectively, respond appropriately, and maintain a mutual comfort level while working with a diverse population., • Ability to translate technical content into actionable insights., • Empathetic and learner-centered approach., • Comfortable in an online environment, navigating LMS platforms (Canvas), Zoom, Slack, or similar environments., • Strong organizational and time-management skills to manage weekly cycles of engagement and support. Program Description and Context: The RAG and Context Engineering: Designing and Building Production-Grade AI Systems program from MIT xPRO is an eight-week learning journey that equips participants to design, evaluate, and deploy retrieval-aware large language model (LLM) systems that perform reliably in real-world environments. In eight weeks, this program will provide participants with expertise in evaluation discipline, system auditing, retrieval-augmented generation (RAG) design, and the core principles that determine whether LLM systems succeed or fail in production. • Duration: 8 weeks (estimated learner commitment: 4–5 hours/week)., • Structure: Blend of asynchronous Canvas activities and live Zoom sessions., • Target Audience: Mid- to senior-level professionals and technical leaders seeking to build end‑to‑end RAG and LLM systems. Emeritus provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal or state laws.

Lead Machine Learning Engineer UK - remote, 35 hour work week Up to £95k + bonus 12m FTC (strong view to go permanent) A professional services firm is looking for a Lead Machine Learning Engineer to join its growing data and AI team. This is a key role focused on building and leading ML engineering capability, delivering scalable AI solutions, and shaping the organisation’s data and AI strategy. The role • Lead the development of machine learning engineering capability across the business, • Design, build, and productionise ML models and data products, • Develop and implement MLOps frameworks (CI/CD, model deployment, monitoring, governance), • Build scalable data and ML pipelines on Azure-based platforms, • Collaborate with data scientists, analysts, and stakeholders to deliver end-to-end AI solutions, • Contribute to data architecture, standards, and best practice across the organisation, • Provide technical leadership, mentoring, and guidance to engineers and wider teams What they’re looking for • Strong experience in ML engineering, MLOps, and data/AI architecture, • Proven track record delivering end-to-end ML solutions in cloud environments (Azure preferred), • Expertise in Python, Spark/PySpark, and modern data platforms (e.g. Databricks), • Hands-on experience with NLP and LLMs, including deployment and optimisation, • Experience building scalable pipelines, model governance processes, and production systems, • Ability to translate business requirements into robust technical solutions, • Strong stakeholder management and leadership experience Why apply • Opportunity to build and shape ML engineering within a growing data function, • High-impact role with ownership of architecture, tooling, and best practice, • Exposure to modern AI and LLM use cases, • Clear pathway to a permanent role Please note: sponsorship is not available for this role.

Senior AI Infrastructure Engineer (OpenStack & Kubernetes) Location: Remote (UK or EU Preferred) Sector: High-Performance GPU Cloud Computing The Opportunity I am representing a fast-growing, international scale-up that is building next-generation GPU cloud infrastructure. This company is the powerhouse behind a high-performance platform designed specifically for the most demanding AI, Machine Learning, and HPC workloads. As they scale their global footprint to meet massive demand, they are seeking a Senior Infrastructure Engineer who enjoys deep technical autonomy. This is a role for a specialist who wants to move fast, solve complex problems, and have direct ownership over the stability and scalability of business-critical systems. What You’ll Be Doing • Owning Infrastructure: Designing, deploying, and operating OpenStack and Kubernetes clusters optimized for multi-tenant GPU workloads., • Driving Automation: Building and maintaining infrastructure-as-code and GitOps practices to ensure seamless scalability., • Optimizing Performance: Enabling reliable workload scheduling through Kubernetes-native tooling, container runtime optimization, and NVIDIA integrations., • Ensuring Resilience: Maintaining high availability and observability through proactive monitoring, logging, and incident response., • Strengthening Security: Implementing strong controls, including RBAC and network policies, to ensure tenant isolation., • Cross-Team Collaboration: Working closely with DevOps, AI, and Product teams to align infrastructure capabilities with customer needs. The Ideal Profile • OpenStack Expert: Significant hands-on experience operating OpenStack in a production environment., • K8s Specialist: Strong experience running production-grade Kubernetes, ideally in bare-metal or private cloud setups., • Systems Generalist: A solid grounding in Linux, networking, and storage with a practical approach to troubleshooting., • Modern Workflows: Experience with infrastructure automation, CI/CD, and Git-based workflows., • Scale-up Mindset: The ability to thrive in a fast-moving environment with a strong sense of accountability. Nice to Have • Exposure to GPU-based infrastructure, large-scale compute platforms, or HPC., • Familiarity with advanced networking technologies., • Contributions to open-source or cloud-native communities. What’s on Offer? • Impact: The opportunity to make a visible, meaningful impact on a platform used by teams running compute-heavy applications., • Flexibility: Flexible working arrangements, including remote or hybrid options., • Growth: Clear career progression and the chance to help shape the company's culture and future., • Culture: A collaborative, transparent, and international culture built on trust., • Benefits: Competitive salary, annual discretionary bonus, 25 days holiday (plus public holidays), and wellbeing benefits.

Background: Agilio Software Group is a leading UK healthcare operations software provider, delivering integrated, mission critical solutions that support primary care, dental, pharmacy, hospital, and veterinary organisations. We have ambitious and exciting growth plans and are looking for talented individuals to be part of our journey. iLearn is our learning and compliance platform, supporting healthcare organisations to meet regulatory requirements, maintain workforce competence, and deliver high quality patient care. The role: As a Lead Software Engineer, you will drive technical direction and product delivery for the iLearn platform - coming in with energy, opinions, and the ability to move fast. You'll lead a cross-functional engineering team, shape our AI strategy, and work closely with Product to define what we build next. You'll combine hands-on technical expertise with people leadership, designing and building scalable, secure, cloud-based solutions that directly support our business objectives. AI is a central theme for us right now. You'll play a leading role in identifying, shaping, and delivering AI-powered features within iLearn, and using AI tooling to accelerate how the team builds and ships software day to day - all working closely with Product to turn emerging capabilities into real user value. Key Responsibilities: • Lead a cross-functional engineering team delivering features and improvements for iLearn - driving pace, quality, and technical direction from design through to deployment and support., • Provide line management and pastoral care for a small team of software engineers, supporting performance, wellbeing, and professional development., • Take technical ownership of the design, development, and maintenance of full stack applications and services underpinning iLearn., • Partner closely with Product to shape the roadmap - contributing technical insight early, challenging assumptions, and ensuring AI and engineering capabilities inform what gets built., • Lead the evaluation, prototyping, and responsible integration of AI and machine learning capabilities into iLearn, including LLM-based features, intelligent automation, and data-driven tooling., • Contribute to planning, estimation, scheduling, and resourcing, helping to deliver work predictably and efficiently., • Communicate technical designs, risks, and progress clearly to senior stakeholders and non technical audiences., • Apply a deep understanding of modern software design patterns and engineering best practices, ensuring solutions are scalable, maintainable, and fit for purpose., • Champion and implement automated testing across functional, acceptance, performance, and security domains to ensure quality is built in from the outset., • Work closely with platform, product, and operations teams to ensure systems are observable, resilient, operationally sound, and secure., • Design and develop cloud deployable services, continuously improving application architecture and infrastructure where appropriate., • Act as a technical authority, leading design discussions, reviewing and approving code, and diagnosing and resolving complex issues., • Build, maintain, and improve CI/CD pipelines to support reliable, automated deployment of products and services., • Promote a strong engineering culture, encouraging best practice, collaboration, and continuous improvement across the team., • Share knowledge and emerging technical insights - particularly around AI developments - with the wider engineering community and mentor junior engineers to support their growth., • Support the growth of the team by participating in recruitment and onboarding of new engineers., • Maintain clear and appropriate technical documentation to support long term maintainability and knowledge sharing. Essential • Minimum of 5 years’ experience in software engineering, • Strong experience as a Senior or Lead Full Stack Software Engineer, • Proven experience leading engineers and delivering software end to end, • A track record of driving delivery with urgency — not just maintaining, but pushing teams and products forward, • Demonstrable experience working closely with Product — influencing roadmap, shaping requirements, and bridging technical and commercial priorities, • Hands-on experience with AI/ML integration — whether LLM APIs, prompt engineering, RAG architectures, or embedding AI tooling into production software, • Deep understanding of modern software design patterns and best practices, • Hands on experience with cloud based architectures and services, • Strong knowledge of CI/CD pipelines and automated deployments, • Experience building scalable, resilient, secure, and observable systems, • Commitment to code quality, maintainability, and testing, • Confident code reviewer and technical decision maker, • Ability to mentor engineers and support their development, • Strong communication skills with technical and non technical stakeholders Agilio operates in regulated, mission critical healthcare environments. You’ll need: • The ability to translate complex business domains into technical solutions, • Awareness of security, resilience, and operational risk, • A mindset focused on reliability and quality, not just feature delivery, • An understanding of how to deploy AI responsibly in regulated, patient-facing contexts Additional Information Job type: The role is remote with occasional travel to one of our offices on an ad-hoc basis. Salary: Competitive + generous benefits Income Protection Life Assurance Enhanced pension Health Cash plan 28 days annual leave + bank holidays Sick pay scheme A range of flexible benefits available through our Agilio Flex portal If you feel you have what it takes to join our team, we look forward to receiving your application!

AI Engineer (ML, Engineer, LLM's, MCP) Location: Fully Remote, UK Salary - Highly competitive plus 15% annual bonus based on personal performance Reporting to: Chief Executive Officer Neulinx have partnered with an established global SaaS company to appoint an AI Engineer for a business-critical role reporting directly to the CEO. This is a high-impact opportunity for an experienced AI Engineer to lead the practical adoption of AI across a 50 person engineering team and the organisation, supporting both internal capability and external product development. Role Overview The successful AI Engineer will play a central role in helping the business evolve towards a more AI-driven future. This position requires a strong blend of machine learning knowledge, software engineering capability, and the ability to apply AI in practical, commercial environments. This is not a managerial position. It is a hands-on role for an AI Engineer who can lead through technical delivery, influence engineering teams through credibility, and help embed AI capability across the wider business. The role will focus on integrating AI into an existing SaaS platform, modernising legacy systems, and identifying opportunities to improve products, workflows, and operational efficiency through the use of AI. Key Responsibilities • Act as the lead AI Engineer within the business, driving the adoption of AI across engineering, internal operations, and customer-facing applications, • Design, build, and deploy AI-powered solutions within an established SaaS environment, • Work with LLMs in real-world product and operational use cases, • Apply prompt engineering techniques to improve workflows, outputs, and user experience, • Build and implement MCP services and advanced AI workflows, • Support the transition of legacy systems towards a more AI-driven architecture, • Partner closely with software engineers to help develop AI capability across the team, • Identify and deliver practical AI and ML use cases that create measurable business value, • Work directly with the CEO and senior leadership team on the company’s AI direction and implementation priorities Candidate Profile The ideal candidate will be an experienced AI Engineer with a strong grounding in machine learning and a proven ability to write high-quality production code. Applicants should be able to demonstrate: • Proven experience in an AI Engineer, ML Engineer, or similar hands-on role, • Strong software engineering skills and the ability to build production-grade systems, • Strong experience with LLMs, prompt engineering, and MCP, • Experience implementing AI solutions within existing or legacy platforms, • The ability to operate effectively in a hands-on, high-visibility role, • Confidence working directly with senior leadership as well as technical teams, • A practical, delivery-focused mindset with a strong bias towards execution, • The ability to influence others and encourage wider AI adoption through hands-on support and technical leadership Additional Context This role is particularly well suited to an AI Engineer who is energised by seeing their work have tangible impact at scale, rather than solely within internal teams. It will also suit someone who is comfortable working within complexity and legacy environments. Existing technologies include MS SQL, C#, JavaScript, and an ongoing React migration, so resilience and a genuine interest in modernising established systems will be important. If you are an AI Engineer who wants to build, influence, and help transform a global SaaS platform through AI, we’d love to hear from you.

Position Overview: SBS is seeking a skilled AI Engineer to join its Data & AI / Engineering organization in the UK or EU. This role will focus on designing, building, and deploying AI-driven solutions that enhance SBS products and client offerings. The ideal candidate will combine strong software engineering fundamentals with applied AI/ML expertise, enabling the development of scalable, production-grade AI systems in a regulated financial services environment. Location: UK or EU Hybrid/Remote: Remote (Occasional travel required) Responsibilities: AI Solution Development • Design, build, and deploy AI/ML models and intelligent applications across SBS platforms, • Develop solutions leveraging:, • Machine Learning (ML), • Natural Language Processing (NLP), • Generative AI (GenAI / LLMs), • Translate business requirements into technical AI solutions that deliver measurable impact Model Deployment & MLOps • Implement and manage end-to-end ML pipelines, from data ingestion to model deployment and monitoring, • Collaborate with DevOps and engineering teams to ensure scalable, reliable production deployment, • Maintain and optimize model performance, accuracy, and efficiency over time Product Integration • Integrate AI capabilities into core banking, payments, and digital platforms, • Work closely with Product Managers, Architects, and Developers to embed AI into customer-facing solutions, • Support API development and microservices architecture for AI-driven features Data Engineering Collaboration • Partner with data engineers to ensure data quality, availability, and pipeline integrity, • Work with structured and unstructured datasets across large-scale, distributed systems Innovation & Continuous Improvement • Stay current with advancements in AI, GenAI, and emerging technologies, • Contribute to experimentation, prototyping, and innovation initiatives, • Identify opportunities to improve automation, efficiency, and decision-making through AI Qualifications: Software Architecture & Design • Application architecture: Strong grasp of clean/hexagonal architecture, dependency injection, SOLID principles, and protocol-based interfaces. Can design well-structured Python services with clear separation of concerns, testable components, and maintainable codebases. This is not optional — the existing system follows these patterns, and new code must be consistent., • API design: Experience designing and maintaining RESTful API contracts. Understands OpenAPI specifications, versioning strategies, schema evolution, and backward compatibility. Can own the API surface that internal consumers depend on., • System design: Distributed systems thinking — understands event-driven patterns, asynchronous communication, eventual consistency, and the trade-offs of different integration approaches. Can reason about how components interact across service boundaries., • Data modeling: Can design domain models, define data flows between system components, and make pragmatic schema design decisions. Understands how data structures affect downstream consumers and the system's evolution. AI & LLM Application Skills • LLM application development: Hands-on experience building production applications powered by LLMs. Must go beyond API calls — RAG pipelines, chain-of-thought reasoning, structured output parsing, multi-step workflows. Candidates who have only fine-tuned models or only called a single provider’s API do not qualify., • Model-agnostic design: This is a sovereign AI system. The candidate must design against standardized API interfaces (OpenAI-compatible, LiteLLM, or equivalent abstraction layers), not couple to any single provider. Must understand model routing, fallback strategies, and how to build systems that can swap underlying models without application-layer rewrites. Experience limited to a single commercial API (OpenAI, Google, Anthropic) without abstraction is insufficient., • Agentic system design: Demonstrated experience designing multi-step AI systems where the model makes decisions about what to do next. This could be via LangGraph, CrewAI, AutoGen, custom agent loops, or any framework — the underlying patterns (ReAct, plan-and-execute, reflection) matter more than the tool., • Prompt engineering depth: Can demonstrate iterative prompt development for complex tasks. Understands few-shot, chain-of-thought, XML/structured prompting, and the behavioral differences between model families and sizes. Critically, understands that prompt strategies must adapt when moving between frontier and smaller OSS models. Python Engineering Production Python: Strong async Python with FastAPI or equivalent framework. Comfortable with Pydantic for data validation, SQLAlchemy for data access, and structured logging (structlog). Writes clean, testable, well-documented code with proper type hints. This is a software engineering role that builds AI systems — not a data science role that happens to write Python. Safeguards for hallucinated tools, loops, partial completion, and unsafe actions. Understands async trade-offs, batching, streaming, and latency accumulation Engineering Qualities • Works within existing systems: The candidate joins a substantial existing codebase and architecture. They must be comfortable reading, understanding, and extending code they did not write — not lobbying to rewrite it., • Production mindset: Thinks about error handling, retry logic, graceful degradation, observability, and security as first-class concerns. Understands that agentic autonomy creates new failure modes that must be anticipated., • Clear communicator: Can explain technical trade-offs to non-technical stakeholders. Can write clear design documents. Can articulate why an agentic approach is or is not appropriate for a given problem. Company Overview At SBS, we’re more than just a technology company; we’re a global fintech partner helping banks and financial institutions transform, innovate, and grow. With over 5,000 employees worldwide and clients in more than 80 countries, our solutions power everything from digital banking and lending to payments and core banking systems. As part of 74Software, we’re backed by a group of leading software companies delivering mission-critical solutions worldwide. Our focus is on delivering long-term value, leveraging cutting-edge technology, and fostering strong client partnerships. Join us and be part of a collaborative, forward-thinking team shaping the future of finance. Why SBS? At SBS, we’re committed to supporting our employees in every aspect of their lives, from health and wellbeing to financial security and lifestyle perks. We offer benefits that help you thrive at work and beyond, including health coverage, retirement plans, paid time off, flexible work options, career development, competitive pay, and global culture perks. Equal Opportunity Employer We are committed to providing equal opportunities and ensuring a fair and inclusive recruitment process. We do not discriminate on the basis of age, disability, gender, sexual orientation, race, religion, or any other protected characteristic.

We are seeking a highly skilled and innovative Agentic AI Engineer to join our team and drive the development and deployment of cutting-edge generative AI solutions within the Microsoft ecosystem. This position is well-suited for candidates with a background in software engineering, data science, or machine learning who excel at developing production-grade AI applications utilizing Microsoft platforms such as M365, Copilot Studio, and Azure AI Foundry, and have at least one year of relevant experience. Strong software development background with proficiency in Python. • Experience with API development using FastAPI, Flask, or Django., • Knowledge of Docker and containerized deployments., • Hands-on experience with LLM models such as OpenAI GPTs, Claude, Gemini, LLaMA, or Mistral., • Expertise in applying prompt engineering techniques to improve model performance and reliability., • Experience in implementing robust evaluation frameworks and Responsible AI (RAI) practices., • Familiarity with Microsoft GenAI/Agentic AI ecosystem such as M365, Copilot Studio and Azure AI Foundry., • Strong understanding of software engineering principles and best practices., • Ability to work in agile environments and collaborate with cross-functional teams. You'll stand out if you also meet any of the following: • You are good at prototyping and experimenting with emerging technologies to assess feasibility and impact., • You have knowledge of vector databases, RAG architectures and their integration into enterprise systems, • You have experience with GenAI development frameworks or orchestration tools such as Semantic Kernel, AutoGen, LangGraph, LangChain, or PromptFlow., • You are familiar with core agent communication protocols, including MCP or A2A., • You are a person who loves to stay current with the latest advancements in GenAI, LLMs, and AI frameworks., • You are Microsoft Certified in Azure AI Engineer Associate or Azure AI Fundamentals. 🛠️ Qualifications • Bachelor's in computer science, data science, or a related field About Avanade: Avanade is the leading provider of innovative digital, cloud, and advisory services, industry solutions, and design-led experiences across the Microsoft ecosystem. The company was founded 25 years ago as a joint venture between Accenture and Microsoft. Back then, digital transformation, automation, and AI weren’t mainstream topics—Microsoft was primarily known for Office 365. But Avanade evolved with the times and is now the number one transformation leader within the Microsoft ecosystem. We have a team of 61,000 professionals in 26 countries. We’re a truly global company with a strong local presence— what I like to call “GLOCAL”: making global impacts on a local level.

Moodsonic uses sound to improve how indoor spaces feel. Our platform delivers adaptive soundscapes for workplaces, hospitals, universities, and other shared environments shaping daily life, integrating with hardware, building systems, and an array of applications to respond dynamically to activity levels, time of day, environmental sensors, and user input. The work sits at the intersection of audio, real-time systems, and human experience. The role We are hiring a Senior Software Engineer to own the backend that the entire product stack sits on: services, data layer, identity and authentication infrastructure, partner-facing integration APIs, device communication, and the security posture. You will own, evolve, and build the systems that power our internal tooling, customer-facing applications, partner integrations, and hardware deployments, strengthening what is already in production and shipping what comes next. You will be the technical lead on production engineering, security, and code quality, building on the foundations the team has put in place. As Moodsonic scales, you will keep the platform safe, reliable, and defensible. You are joining a team where colleagues hold deep domain knowledge. You will need to build trust, collaborate well, and lead through influence rather than authority. This is not a management role. The platform is live and growing quickly, with real customers and real consequences. What you'll work on In your first six to twelve months: • Own and evolve the backend platform: services, data layer, infrastructure, APIs. Strengthen what is in production today, design what is missing, and build what comes next, • Own the backend side of how our deployed hardware connects to the platform: ingestion, device authentication, fleet management, and remote provisioning. Visibility and input into on-device code decisions, because device security is platform security, • Own the identity, authentication, and account layer of the platform, • Own and operate our data protection posture across the platform: encryption in transit and at rest, key management, data lifecycle, and recovery, • Own the partner-facing integration APIs end to end, from design through operation. These are the surfaces our customers and hardware partners build against, and their reliability is our reputation, • Own the engineering practices that support our certifications and audit-readiness, • Establish and maintain the engineering standards (testing, review, deployment, monitoring, secure coding) that the team operates by, • Partner with the engineers owning the audio engine and frontend surface on the backend contracts their work depends on What we are looking for Required: • 5+ years shipping and operating production backend systems, including time on-call and in incident response. You know what it feels like when something breaks at 2am and you own the fix, • Operational resilience as a habit: you design for failure, build with recovery in mind, and treat incident learning as a driver of engineering quality, • Strong judgment in small-team environments. You have owned quality yourself rather than inheriting it from process. You can take high-level product, customer, or security needs and turn them into practical technical plans without a big PM or architecture layer handing you a spec, • Deep relational data modeling and schema design. Postgres or equivalent as a daily tool. Strong instincts for migrations, indexing, and query performance under load, • API design experience: you have built and maintained APIs that outlived their first version and you have opinions about versioning, compatibility, and contract discipline, • Identity and authentication systems experience: modern identity protocols (OAuth or similar), session management, role-based access, multi-tenant boundaries. You understand what breaks when these are wrong, • Security mindset in practice, not theory. You think about attack surface, threat models, and access control as a matter of course, with working knowledge of cryptography and data protection fundamentals, • Code quality and observability as habits. Tests, substantive review, documentation, and the instinct to measure how software behaves in production are part of doing the work, not chores after it, • Strong Python for backend services. Comfortable with SQL, Docker, at least one major cloud, infrastructure as code (Terraform, Pulumi, or equivalent), and modern CI/CD practices, • Modern AI development tools are part of how you ship. You stay current as they evolve, adopt what adds value, and use AI to go faster on work you already understand, which is why you catch AI mistakes before they become bugs, • Demonstrated technical leadership through influence, not authority: you raise the bar through code review, standards, and example, and you have earned trust from engineers who were there before you, • Pride in craft, proactive risk-flagging, and the instinct to raise quality bars rather than work around them. Intellectual honesty and the willingness to push back when the right answer is unpopular, • Clear written and verbal communication, particularly when working asynchronously across time zones Valued: • Designing systems that interface with deployed hardware: device fleets, provisioning flows, secure OTA updates, telemetry ingestion, • Shipping to enterprise customers, incident response commitments, and contractual security obligations, • Experience inside a compliance-driven environment (SOC 2, ISO 27001, HIPAA, or equivalent) or building for auditability as a default, • Kubernetes and modern container orchestration, • Additional backend language fluency (Node or TypeScript, Go, Rust) for polyglot service work, • Audio, signal processing, or real-time systems background, • AI and machine learning in product contexts: audio generation, personalization engines, training and serving pipelines Not required but welcome: • Interest in sound, music, acoustics, or the wellbeing applications of audio Team and how we work You will join a small, senior team distributed across the UK, Europe, and the US West Coast. We run a weekly product cadence, work asynchronously by default, and rely on clear written communication to stay aligned across time zones. Compensation and benefits Base salary £65,000 to £85,000, calibrated to experience. Equity will be a material part of the package. Benefits include private medical insurance for UK employees, 28 days paid holiday inclusive of UK holidays, flexible remote-first working. UK right to work is required. How to apply Send a short note, your CV, and links to work you are proud of. Please include three to five sentences on a production system, API, identity/auth, or platform hardening project you owned.

Looking for an AI Test Manager/Lead with hands-on experience in testing AI applications, including Agentic AI systems, AI agent testing, and validation. Must have: • Experience of testing AI applications, • Experience of test automations and tools, e.g. Tosca, Python, Selenium, • Strong knowledge & use of QA methodologies e.g. Agile, Waterfall, DevOps, BDD for functional test activities., • Proven experience as a Quality Assurance Engineer, with a significant focus on testing Artificial Intelligence and Machine Learning products., • Agentic AI Agent testing and validation., • Strong knowledge of Responsible AI principles and practices, including experience in testing for fairness, bias detection, explainability, privacy, and security in AI systems., • Familiarity with Agentic AI concepts and architectures.

Data Scientist / Machine Learning Engineer – Defence & Security Bristol, London, Manchester DV Cleared Required The Opportunity Join a growing Data Science & Machine Learning team working on some of the most ambitious and mission-critical programmes in the Defence & Security sector. This role offers the chance to apply cutting-edge AI techniques to real-world challenges, delivering impactful solutions that support national security. Key Responsibilities • Apply data science, machine learning, and AI techniques to solve complex, real-world problems, • Research, design, and implement innovative models and solutions, • Work across the full ML lifecycle from requirements gathering and prototyping to deployment and live service support, • Deliver high-quality, scalable solutions with measurable impact, • Collaborate with multidisciplinary teams in agile environments, • Contribute to new ideas, propositions, and project delivery, • Build strong relationships with stakeholders and communicate insights effectively Essential Skills & Experience • Proven experience applying data science or machine learning in Defence, Security, public sector, or academia, • Strong understanding of machine learning models (e.g. Transformers, CNNs, Generative AI) and their practical applications, • Excellent communication skills with the ability to present complex ideas clearly, • Experience working with stakeholders and cross-functional teams, • Track record of contributing to project delivery, innovation, or capability development Desirable Skills • Experience working with text, audio, image, or video data, • Familiarity with cloud platforms (AWS, Azure, GCP), • Strong Python skills and experience with ML libraries and frameworks (e.g. TensorFlow, PyTorch), • Knowledge of statistics and probability, • Experience with ML lifecycle tools (e.g. MLflow, Kubeflow, Argo), • Understanding of Ethical and Responsible AI principles Security Requirements You must hold active UK Developed Vetting (DV) clearance.

Location: Remote (UK or Greece) Salary: Competitive, based on experience Job Type: Full-Time Working for Krotos We revolutionize sound creation by making Hollywood-quality sound accessible to everyone. Our groundbreaking software, featured in blockbuster productions like Avengers and Game of Thrones, empowers creators to design high-quality sound faster and more intuitively. Our mission is to change the way people design and perform sound. As a fast-growing, remote-first company, we are pushing the boundaries of creativity and innovation in content creation. The role Join our R&D team as an ML specialist to research, develop and ship technologies that change how people create sound. We're building systems that understand, manipulate and generate audio in ways that feel genuinely intuitive to professionals and we're nowhere near done. You'll own problems end-to-end, from identifying the right approach to getting it in front of customers, working closely with product to make sure what we build actually matters. Key objectives • Research and develop multimodal AI technologies that improve the way people work with sound, • Build and optimise LLM-powered audio pipelines and extend our Qwen-based vision model for audio production use cases, • Identify opportunities to apply the latest advances in generative AI and multimodal research to the professional audio field Responsibilities • Work within the team and research engineers to solve problems for film makers & sound designers, • Design and maintain backend inference systems that meet the latency and quality demands of professional audio workflows, • Collaborate with product and engineering teams to implement ML research in commercial products, • Work with the product owner to identify where ML creates the most value for customers, • Clearly and effectively communicate ML concepts, model behaviour and tradeoffs to the wider business, • Provide technical guidance on model architecture, fine-tuning strategy and deployment decisions Skills and experience Essential: • A degree in a relevant field or extensive professional experience, • Experience in commercial machine learning research and development, • Strong hands-on experience fine-tuning and adapting large language models (LoRA, QLoRA, PEFT, DPO/RLHF), • Experience working with data, training and evaluating machine learning models, • Experience with multimodal architectures — audio-language, vision-language, or both, • Extensive audio and signal processing knowledge — spectral features, neural codecs, generative audio models, • Experience deploying models to cloud inference (AWS or GCP) with awareness of latency and cost tradeoffs, • MLOps competency — experiment tracking, model versioning, evaluation pipelines, ML CI, • Experience with Python and modern ML frameworks (PyTorch, JAX), • Excellent verbal and written English communication skills, • Excellent analytical and problem-solving skills, • A desire to innovate and push current practice Desirable: • Experience with vision-language models, particularly Qwen-VL or similar, • Experience with Agile software development practices, • Familiarity with VST/AU plugin architectures and real-time audio constraints, • Experience delivering ML technologies shipped in commercial audio software, • Knowledge of sound design and audio post-production workflows, • C++ reading ability, • Previously registered audio machine learning patents Team Core Values Inventive. Driven. Transparent. Our values define who we are and how we work: • Honesty & Transparency: We communicate openly, share the truth even when it’s difficult, and build trust through clarity, • Team Player: We collaborate, support each other, and put collective success above ego, • Problem Solver: We face challenges head-on and find creative, practical solutions., • Open-Minded: We listen to others, consider different perspectives, and recognise the complexity of good decisions, • Politeness & Respect: We treat colleagues and customers with courtesy and professionalism, • Curiosity & Growth: We love learning, experimenting, and continuously improving, • Data-Driven: We let insights and evidence guide our decisions, not guesswork, • High Standards: We take pride in excellence and pay attention to the details that matter, • Strong Work Ethic: We commit, follow through, and work hard to achieve ambitious goals Benefits • Competitive salary and benefits package, • Private health insurance, • Opportunities for professional growth and development, • Flexible, remote working environment, • Access to cutting-edge technology and tools, • Exciting projects in a fast-growing, innovative company Next steps Send your CV and a cover letter to admin@krotosaudio.com explaining why you are the best candidate for this role, referencing the requirements above and including two to three brief examples of relevant results. Note: All offers are subject to eligibility to work in the UK or Greece and satisfactory references. At Krotos, we value diversity and are committed to fostering an inclusive environment. We encourage applications from candidates of all backgrounds. Reasonable adjustments are available throughout the application and interview process.

Lead ML Engineer (12-month FTC) £80,000 - £90,000 Remote (UK Based Only) This is a rare opportunity to step into a senior, hands-on ML Engineering role where you will shape how machine learning is delivered, scaled, and embedded across a large, complex organisation. THE COMPANY They are a large, well-established professional services organisation with a strong reputation for quality, trust, and long-term client relationships. Data and AI are a strategic priority, with significant internal backing to move from successful proof of concepts to robust, production-grade platforms. THE ROLE As a Lead ML Engineer, you will take ownership of ML Engineering delivery end-to-end, helping define best practice while remaining highly hands-on. Specifically, you can expect to be involved in the following: • Leading the ML Engineering capability and contributing to the wider data and AI strategy., • Designing, building, and productionising ML pipelines aligned to business goals., • Delivering NLP and LLM-driven solutions, including fine-tuning and deployment., • Implementing strong MLOps practices across model training, deployment, and monitoring., • Working closely with Data Scientists to support, maintain, and improve models in production., • Building APIs and data products that enable ML solutio...

Machine Learning Engineer with generative AI, LLM or ML experience is sought by a high growth scale up based near Birmingham. Working at the forefront of national security innovation this Machine Learning Engineer will work within a R&D team collaborating with industry partners to turn ideas into production ready, market leading solutions. This role would suit a software engineer with a couple of years commercial experience within broad range of technologies and a demonstratable passion for AI/ ML innovation who is looking for a truly collaborative, autonomous working environment with end to end project exposure. In return this Machine Learning Engineer can expect excellent career development and training opportunities within a market leading SME. Given the nature of the work all successful candidates will need to be British citizens This Machine Learning Engineer should have most of the following key skills: - A software or data engineering background - Python, JavaScript, Typescript node.js etc - A real passion for bleeding edge generative AI and/or advanced machine learning technology - Pytorch, TensorFlow, LlamaCPP, Keras etc - Varied database exposure - PostgreSQL, MongoDB, CosmosDB - Cloud services exposure - AWS preferred but all considered - Very strong communication skills - Experience working in R&D or small technical teams would be a plus This Machine Learning Engineer will receive - Start...

Machine Learning Engineer with generative AI, LLM or ML experience is sought by a high growth scale up based near Birmingham. Working at the forefront of national security innovation this Machine Learning Engineer will work within a R&D team collaborating with industry partners to turn ideas into production ready, market leading solutions. This role would suit a software engineer with a couple of years commercial experience within broad range of technologies and a demonstratable passion for AI/ ML innovation who is looking for a truly collaborative, autonomous working environment with end to end project exposure. In return this Machine Learning Engineer can expect excellent career development and training opportunities within a market leading SME. Given the nature of the work all successful candidates will need to be British citizens This Machine Learning Engineer should have most of the following key skills: • A software or data engineering background - Python, JavaScript, Typescript node.js etc, • A real passion for bleeding edge generative AI and/or advanced machine learning technology - Pytorch, TensorFlow, LlamaCPP, Keras etc, • Varied database exposure - PostgreSQL, MongoDB, CosmosDB, • Cloud services exposure - AWS preferred but all considered, • Very strong communication skills, • Experience working in R&D or small technical teams would be a plus This Machin...

Senior Data Engineer (Azure / Microsoft Fabric / AI) Birmingham Hybrid 3 days per week £60,000 to £70,000 + Bonus + Excellent Benefits We are recruiting for a Senior Data Engineer to join a growing data team within an leading wealth management organisation undergoing significant technology transformation, with strong investment in Azure, Microsoft Fabric and AI-driven data capabilities. This role offers the opportunity to work on a modern data platform while also contributing to how machine learning and AI-driven insights are integrated into production environments. You will play a key role in shaping how data is used across the business, combining hands-on engineering with technical influence. Key Responsibilities Design and deliver scalable Azure-based data pipelines and ETL workflows Build and optimise data models supporting analytics and reporting Support and enhance Azure Synapse and Azure Data Lake environments Contribute to the migration and adoption of Microsoft Fabric Integrate machine learning and AI-driven outputs into data pipelines Develop and support Power BI datasets and reporting layers

AI Engineer Placement Programme no experience needed From £45,000 to £75,000 per annum AI Trainee Engineer £45,000£75,000 Job Programme This is a self-funded programme that leads to employment, fees apply. Job GuaranteeComplete the programme and get a job, or get your course fees back. Location:UK Wide (Remote Opportunities Available) Looking to start a career in AI Engineering? We are offering a structured pathway into AI Engineering, designed to help you enter one of the fastest-growing sectors in tech with no prior experience. This opportunity includes training, support, and access to our specialised recruitment support for job roles across the UK. No prior experience required. Train online at your own pace and become job-ready in as little as afew weeks. Our programme includes: • Official AWS Certified Cloud Practitioner certification, • Training in Python, Machine Learning, and AI systems, • Hands-on projects using real-world AI tools and technologies, • Professional CV and LinkedIn support, • Interview preparation, • Dedicated recruitment support until placed, • Personalised 1-1 tutor support, • Hands-on projects to build your AI portfolio Flexible, affordable, achi...

As part of our continued investment in AI and emerging technologies, we are looking for an AI Engineer to join our growing Technology team. This is an exciting opportunity for someone early in their career who is passionate about applied AI and looking to make a real impact across a multi-disciplinary business. The Role: Working closely with our Head of Technology Delivery and wider Technology team, you will support the design, prototyping and implementation of AI-enabled solutions that deliver measurable business value. As Ridge develops its AI strategy and roadmap, you will play an important role in helping to deliver innovative solutions across the business. You will gain exposure to the full lifecycle of AI initiatives, supporting projects that include intelligent automation, Copilot-enabled workflows, advanced analytics and emerging machine learning capabilities. This is a hands-on role, ideal for someone curious about new technologies, including AI agents, and comfortable working at both a conceptual and detailed level. Key Responsibilities: • Support stakeholders in translating business requirements into AI-driven solutions, • Identify opportunities to apply AI technologies, including Copilot, automation and agentic workflows, • Assist in the development and testing of AI models, prompts and workflows, • Evaluate the feasibility and potential impa...

Competitive Advantages, Customer Solutions, Design, Development Testing, Enterprise Architecture Framework, Generative AI, Machine Learning (ML), Quality Engineering, Risk Assessments, Software Quality Engineering, Technical Knowledge. As a Senior Technology Engineer within PNC's Technology organiza

CHH Conex operates at the heart of key vertical markets, delivering connectivity solutions which power almost every industry, contributing towards smart city transformation. We are a leading provider of bespoke cable assemblies, integrated cabinets and managed services that support engineers in the field. We operate in several diverse vertical markets (including Utilities and Solar), delivering a range of connectivity solutions and consumables that help drive smart city transformation, innovation and productivity. We are looking for a Maintenance and Design Engineer to join our team in a unique hybrid role combining hands-on maintenance engineering with mechanical, electrical and design engineering activities. This position plays a key role in maintaining operational uptime across machinery and facilities, while also designing and developing engineered solutions to support both customer and business needs. This role offers variety, responsibility and the opportunity to work across maintenance, design, prototyping and continuous improvement. The Role You will provide engineering support across: Machinery breakdown response, fault-finding and repair Planned preventative maintenance and site maintenance Mechanical, electrical and basic PCB design CAD modelling, technical drawings and engineering documentation You will work with machine shop equipment, CNC machinery and CAD systems, while managing parts and documentation through a PDM/PLM system. Key Responsibilities Maintenance & Fault-Finding Maintain the operational availability of machinery, tooling and equipment Assess faults, diagnose root causes and carry out effective repairs Troubleshoot mechanical systems under time pressure Apply structured problem-solving to restore equipment safely and efficiently Preventative & Site Maintenance Carry out scheduled inspections, calibration and preventative maintenance Perform planned repairs and cleaning to minimise downtime Undertake basic site maintenance including plumbing, heating, lighting, electrics and carpentry Support HVAC systems including chillers, air conditioning and fan-based cooling Ensure all work is conducted in line with safety standards and regulations Design & Development Interpret customer requirements and develop practical engineering solutions Produce complex 3D models and manage large assemblies Create detailed 2D drawings suitable for manufacture Design sheet metal components for external manufacture Build samples and prototypes to validate designs Produce basic electrical schematics, wiring solutions and PCB layouts Engineering Data & Documentation Use SolidWorks 2026 and TurboCAD 2022 for 3D and 2D design Manage parts, revisions, BOMs and Engineering Change Requests within INFOR Use ERP and computerised systems to support scheduling and control Ensure compliance with electrical safety regulations and industry standards Produce high-quality technical documentation, drawings and reports Values Carry out all duties in line with CHHs core values: Driven, Trusted, Agile, People-Focused and Responsible About You Essential 18th Edition (BS 7671) Wiring Regulations Strong mechanical fault-finding and troubleshooting experience Experience planning and carrying out preventative maintenance Hands-on experience with lathes, milling machines, CNC machines and workshop tools Proficiency in SolidWorks 2026 and TurboCAD 2022 Experience creating complex 3D models and detailed 2D manufacturing drawings Knowledge of electrical safety regulations and standards Strong problem-solving skills with the ability to remain calm under pressure Excellent organisation, time management and attention to detail A collaborative, adaptable approach and commitment to ongoing learning TPBN1_UKTJ

Senior Software Engineer Birmingham (Hybrid) Permanent | Full-Time Competitive Salary A growing technology business is seeking a Software Engineer to join its engineering team in Birmingham. This is an excellent opportunity for a developer with strong AWS and backend engineering experience who wants exposure to cloud-native systems, IoT integrations, frontend development, DevOps, and AI-powered applications. Key Responsibilities Design, develop, and maintain AWS-based backend microservices Build frontend applications using React and TypeScript Work on IoT integrations including connected edge devices Develop infrastructure using AWS CDK / Infrastructure as Code Support CI/CD pipeline improvements and deployments Contribute to AI / LLM-powered product functionality Collaborate with stakeholders to define and deliver solutions Maintain code quality through code reviews and engineering best practice Technical Environment Languages: TypeScript, Node.js, Python, Go Cloud: AWS Lambda, API Gateway, EventBridge, SQS, Step Functions Databases: DynamoDB, PostgreSQL, Aurora, MongoDB Frontend: React, TypeScript, MUI DevOps: AWS CDK, Terraform, Docker, GitLab CI, CodePipeline AI: Amazon Bedrock, RAG, LLM integrations Skills Required Commercial software engineering experience Strong AWS cloud/serverless experience Strong backend development skills in TypeScript, Python, or Go CI/CD and Docker experience Full-stack engineering mindset Strong communication skills Desirable Skills React / TypeScript frontend experience Infrastructure as Code GraphQL / AppSync Event-driven architectures IoT / edge systems AI / machine learning feature development Benefits Hybrid working Modern cloud-native technology stack Exposure to AI and emerging technologies High ownership engineering role Collaborative team environment Competitive salary

In this role, you will formulate, train and deploy machine learning models for robotic systems that perceive the world through vision and sensors, learn structured representation in data, and operate reliably in real‑world industrial environments. Strong background in deep learning (computer visio

Principal Machine Learning Engineer. Lead the"end-to-end"development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Expect to in

Principal Machine Learning Engineer. Lead the"end-to-end"development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Expect to in

The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Evaluate emerging research in machine learning, deep learning, and perso

Senior Machine Learning Engineer. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Evaluate emerging research in machine

White Collar Factory (95009), United Kingdom, London, LondonStaff Software Engineer - Machine Learning. Actively mentor and develop engineers, fostering a culture of continuous learning. At Capital One, you'll be part of a community of technical leaders who drive engineering excellence, foster innov