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Job Description COMPANY: Canoe Intelligence WEBSITE: TITLE: Sr. Machine Learning Engineer LOCATION: New York City or London (hybrid) / Fully Remote in the United States or United Kingdom SALARY: $180,000 - $220,000 (based on NYC, will be adjusted for geo) The Role: We are looking for a Senior Machine Learning Engineer to design and deploy models that make sense of highly complex, unstructured financial documents, enabling us to deliver data with unprecedented accuracy, speed, and trust. You’ll work hands-on with LLM and other ML Models, helping scale Canoe’s platform while shaping how alternative investment firms interact with their data. What You’ll Do: * Design, train, and evaluate ML models for document classification, entity extraction, summarization, and information retrieval. * Fine-tune and optimize large language models for domain specific use cases, optimizing their performance for accuracy, efficiency, and scalability. * Work closely with data engineering teams to preprocess and engineer features from large datasets to enhance the performance of machine learning models. * Build scalable, production-ready ML services with strong observability, monitoring, and retraining capabilities. * Contribute to Canoe’s MLOps stack, including CI/CD for models, feature stores, evaluation frameworks, and data versioning. * Collaborate with product managers, software engineers, and other stakeholders to integrate machine learning models into end-to-end solutions. * Stay current with advancements in LLMs, Agentic AI, and ML, and translate new research into practical improvements to Canoe’s technology stack. * Conduct code reviews to ensure code quality and provide mentorship to junior members of the machine learning team. What We’re Looking For: * Minimum of 5 years of experience in applied ML engineering, with a focus on NLP, information extraction, or LLMs. * Proficiency in Python and relevant machine learning libraries (e.g., TensorFlow, PyTorch). * Strong understanding of MLOps (Docker, Kubernetes, CI/CD for ML, experiment tracking). * Proficiency with AI-assisted development tools (e.g., GitHub Copilot, Claude Code agent) to accelerate software development, prototyping, testing, and deployment of ML solutions. * Problem-solver with a product mindset and bias toward outcomes. * Excellent communication skills; able to partner across engineering, product, and business teams. * Comfortable in fast-paced, agile startup environments. * Bachelor’s degree in computer science or related field. Preferred * Master Degree or PhD in computer science or related field * Experience in training and deploying large language models. * Familiarity with cloud computing platforms and distributed computing. * Familiarity with modern ML Ops tools such as Modal, Weights and Biases, Sagemaker, etc. * Experience with LLM fine-tuning techniques such as LoRA, QLoRA, or parameter-efficient training frameworks (e.g., Unsloth). * What You’ll Get: * Medical, dental, vision benefits * Flexible PTO * 401(k) * Flexible work from home policy * Home office stipend * Employee Assistance Program * Gym/Wifi reimbursement * Education assistance * Parental Leave Our Values: * Client First —> Listen, and deliver client-centric solutions * Be An Owner —> Take initiative, improve situations, drive positive outcomes * Excellence —> Always set the highest standard for yourself and others * Win Together —> 1 + 1 = 3 Who We Are: Canoe is reimagining alternative investment data processes for hundreds of leading institutional investors, capital allocators, asset servicing firms and wealth managers. By combining industry expertise with the most sophisticated data capture technologies, Canoe’s technology automates the highly-frustrating, time-consuming, and costly manual workflows related to alternative investment document and data management, extraction and delivery. With Canoe, clients can refocus capital and human resources on business performance and growth, increase efficiency, and gain deeper access to their data. Canoe’s AI-driven platform was developed in 2013 for Portage Partners LLC, a private investment firm. Canoe is an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under federal, state, or local law.

Job DescriptionAbout Quizlet: At Quizlet, our mission is to help every learner achieve their outcomes in the most effective and delightful way. We’re a $1B+ learning platform used by two-thirds of U.S. high school students and half of college students, powering over 1 billion learning interactions each week. We blend cognitive science with machine learning to personalize and enhance the learning experience for students, professionals, and lifelong learners alike. We’re energized by the potential to power more learners through multiple approaches and various tools. Let’s Build the Future of LearningJoin us to design and deliver AI-powered learning tools that scale across the world and unlock human potential. About the Team: The Personalization & Recommendations team at Quizlet is building personalized learning experiences that help millions of learners study more effectively. We are looking for Machine Learning Engineers ranging from the Senior to Staff as well as Sr. Staff levels (note: leveling decisions made through the interview process). You’ll bring strong expertise in modern recommender systems — from deep learning–based retrieval and embeddings to multi-stage ranking and evaluation — and contribute to the evolution of Quizlet’s personalization capabilities. You’ll work at the intersection of machine learning, product, and scalable systems, ensuring our recommendations are performant, responsible, and aligned with learner outcomes, privacy, and fairness. We’re happy to share that this is an onsite position. To help foster team collaboration, we require that employees be in the office a minimum of three days per week: Monday, Wednesday, and Thursday and as needed by your manager or the company. We believe this work environment enhances efficiency, fosters collaboration, and supports growth for both employees and the organization. In this role, you will: • Design and implement personalization models across candidate retrieval, ranking, and post-ranking layers, leveraging user embeddings, contextual signals, and content features., • Develop scalable retrieval and serving systems using architectures such as Two-Tower models, deep ranking networks, and ANN-based vector search for real-time personalization., • Build and maintain model training, evaluation, and deployment pipelines, ensuring reliability, training-serving consistency, observability, and robust monitoring., • Partner with Product and Data Science to translate learner objectives such as engagement, retention, and mastery into measurable modeling goals and experiment designs., • Advance evaluation methodologies, contributing to offline metric design such as NDCG, CTR, AUC, and calibration, and supporting rigorous A/B testing to measure learner and business impact., • Collaborate with platform and infrastructure teams to optimize distributed training, inference latency, and serving cost in production environments., • Stay informed on industry and research trends, evaluating opportunities to meaningfully apply them within Quizlet’s ecosystem., • Mentor engineers, supporting technical growth, experimentation rigor, and responsible ML practices., • Champion collaboration, inclusion, curiosity, and data-driven problem solving, contributing to a healthy and productive team culture., • Depending on level, contribute to broader technical strategy, guide architectural decisions, and influence personalization direction across teams and product surfaces.What you bring to the table:, • Minimum 5+ years of experience in applied machine learning or ML-heavy software engineering, with a strong focus on personalization, ranking, or recommendation systems., • Demonstrated impact improving key metrics such as CTR, retention, engagement, or other learner-facing outcomes through recommender or search systems in production., • Strong hands-on skills in Python and PyTorch, with expertise in data and feature engineering, distributed training and inference on GPUs, and familiarity with modern MLOps practices, including model registries, feature stores, monitoring, and drift detection., • Deep understanding of retrieval and ranking architectures, such as Two-Tower models, deep cross networks, Transformers, MMoE, or similar approaches, and the ability to apply them to real-world problems., • Experience with large-scale embedding models and vector search systems, including FAISS, ScaNN, or similar technologies., • Proficiency in experiment design and evaluation, connecting offline metrics such as AUC, NDCG, and calibration with online A/B test outcomes to drive product decisions., • Clear, effective communication, with the ability to collaborate well with product managers, data scientists, engineers, and cross-functional partners., • A growth and mentorship mindset, helping elevate team quality in modeling, experimentation, and reliability., • Commitment to responsible and inclusive personalization, ensuring our systems respect learner privacy, fairness, and diverse goals.Additional strengths for Senior Staff candidates:, • Experience shaping technical strategy across teams or disciplines, balancing long-term architectural vision with near-term product and business priorities., • Demonstrated leadership through influence, including aligning stakeholders, guiding teams through ambiguity, and driving accountability for outcomes., • Ability to communicate complex technical trade-offs clearly to senior leadership and cross-functional audiences., • Experience mentoring senior engineers or applied scientists and helping raise the technical bar across an organization., • Proven ability to lead large, ambiguous initiatives and influence platform, product, and modeling direction at scale.Bonus points if you have:, • Publications or open-source contributions in RecSys, search, or ranking., • Familiarity with reinforcement learning for recommendations or contextual bandits., • Experience with hybrid RecSys systems blending collaborative filtering, content understanding, and LLM-based reasoning., • Prior work in consumer or EdTech applications with personalization at scale.Compensation, Benefits & Perks:, • Quizlet is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. Salary transparency helps to mitigate unfair hiring practices when it comes to discrimination and pay gaps. Total compensation for this role is market competitive, including a base salary of $175,000 to $330,000 depending on location, level (Senior, Staff, or Senior Staff), and experience, as well as company stock options, • Collaborate with your manager and team to create a healthy work-life balance, • 20 vacation days that we expect you to take!, • Competitive health, dental, and vision insurance (100% employee and 75% dependent PPO, Dental, VSP Choice), • Employer-sponsored 401k plan with company match, • Access to LinkedIn Learning and other resources to support professional growth, • Paid Family Leave, FSA, HSA, Commuter benefits, and Wellness benefits We strive to make everyone feel comfortable and welcome!We work to create a holistic interview process, where both Quizlet and candidates have an opportunity to view what it would be like to work together, in exploring a mutually beneficial partnership. We provide a transparent setting that gives a comprehensive view of who we are! In Closing: At Quizlet, we’re excited about passionate people joining our team—even if you don’t check every box on the requirements list. We value unique perspectives and believe everyone has something meaningful to contribute. Our culture is all about taking initiative, learning through challenges, and striving for high-quality work while staying curious and open to new ideas. We believe in honest, respectful communication, thoughtful collaboration, and creating a supportive space where everyone can grow and succeed together.” Quizlet’s success as an online learning community depends on a strong commitment to diversity, equity, and inclusion. As an equal opportunity employer and a tech company committed to societal change, we welcome applicants from all backgrounds. Women, people of color, members of the LGBTQ+ community, individuals with disabilities, and veterans are strongly encouraged to apply. Come join us! To All Recruiters and Placement Agencies: At this time, Quizlet does not accept unsolicited agency resumes and/or profiles. Please do not forward unsolicited agency resumes to our website or to any Quizlet employee. Quizlet will not pay fees to any third-party agency or firm nor will it be responsible for any agency fees associated with unsolicited resumes. All unsolicited resumes received will be considered the property of Quizlet.#LI-onsite We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Job Description • Role: Senior Data Scientist, • Location: New York City, • Type: Hybrid Position Summary Our client is looking for a Data Scientist who will play a crucial role in providing analytics and data science support to a client within our Sports, Media and Entertainment practice. The primary responsibility of this role is to leverage your expertise in analytics, data science, machine learning and AI to empower the client in making informed business decisions. You will work with a dynamic team and will have true ownership and impact over developing analytics solutions and data products for the stakeholders. If you're a passionate sports fan who understands both the emotional and commercial dynamics of the industry - and you thrive in fast paced, collaborative environments, we'd love to connect. Responsibilities: • Collaborate with the client in the sport sector to understand their business objectives and challenges and ensure the delivery of high-quality analytics/data science solutions., • Design and build end to end machine learning solutions and statistical frameworks across fan behavior., • Own the full modeling lifecycle: problem framing, feature engineering, model selection, cross validation and hyperparameter tuning, • Lead recurring analytical programs with a focus on reproducibility and automation., • Partner with data engineering to integrate model outputs into operational systems and stakeholder facing products., • Utilize your strong analytical and problem-solving skills to extract meaningful insights from data and contribute to data-driven decision-making., • Use variety of analytical tools (SQL, Python) and techniques (regression, decision trees, machine learning concepts etc.) to carry out analyses, create ML models and drive conclusions., • Support the integration of data science capabilities for the client to help solve tangible problems with measurable impact., • Bachelor's degree in economics, mathematics, computer science/engineering, operations research or related analytics areas, • 2+ years of hands-on experience in a data science role with a track record of shipping models into production., • Extremely proficient in SQL for robust data extraction and analysis., • Strong programming skills in Python., • Familiarity with Git and code/data version control., • Solid statistical foundation, • Exposure to NLP techniques for processing unstructured survey data., • Excellent communication, problem-solving, and critical thinking skills., • Self-started and willingness to take on challenging initiatives, • Effective time management and attention to detail, • Master's degree in a relevant field (e.g., Data Science, Analytics, Business Analytics)., • 4-5 years experience, • Industry experience in Sports or Media., • Familiarity with additional data analysis and visualization tools., • Advanced statistical analysis and modeling skills., • Familiarity with data science governance practices

Job Description About the job Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey. Position: MLOps Engineer (JAX, PyTorch, Pallas/Triton) Type: Contract Compensation: $90–$130/hour Location: Remote Role Responsibilities • Guide research and engineering teams to close knowledge gaps and improve AI model performance in MLOps, training infrastructure, and ML framework-level topics., • Design challenging, domain-relevant tasks across multiple specializations. Write accurate and well-structured solutions to MLOps and ML systems problems., • Evaluate MLOps tasks and solutions. Provide clear, written technical feedback., • Develop guidelines and detailed rubrics/evaluation frameworks to assess training pipeline design, distributed systems reasoning, and kernel-level optimization across tasks. Must-Have • 5+ years of dedicated professional experience in ML infrastructure, MLOps, or ML systems engineering at a recognized, top-tier organization., • Hands-on production experience with JAX and/or PyTorch at scale, including distributed training strategies (FSDP, tensor parallelism, pipeline parallelism), memory optimization, and framework-level debugging., • Experience writing or optimizing custom GPU kernels using Pallas (JAX) or Triton, including tiling strategies, memory layout design, and kernel fusion., • Demonstrable career progression., • Ability to engage reliably for at least 30 hours/week during weekdays., • W-2 employment with Cincinnatus LLC., • Upload resume, • AI interview based on your resume

Job Description Datavant is the data collaboration platform trusted for healthcare. Guided by our mission to make the world's health data secure, accessible and actionable, we provide critical data solutions for organizations across the healthcare ecosystem - including providers, health plans, researchers, and life sciences companies. From fulfilling a single patient's request for their medical records to powering the AI revolution in healthcare, Datavanters are building the future of how data is connected and used to improve health. By joining Datavant today, you're stepping onto a driven and highly collaborative team that is passionate about creating transformative change in healthcare. The VP of Data & ML Platforms is a senior executive accountable for the strategy, architecture, and delivery of Datavant's enterprise data and ML platform. This role owns the full data stack, from ingestion and storage through governance, compute, and AI/ML enablement, ensuring that Datavant's data assets are architecturally sound, well-governed, and positioned to scale through organic growth and acquisition. This is not a governance-only position. The VP sets architectural direction, makes definitive technology decisions, and builds a high-performing engineering organization capable of operating at enterprise scale in a regulated healthcare environment. The role has authority over data platform architecture, governance standards, and AI infrastructure strategy, and is accountable for reliability, architecture maturity, governance adoption, and integration readiness Key Responsibilities Data Platform Architecture & Strategy • Own the long-term enterprise data architecture, including the evolution of the company's data lake, cloud data warehouse, and clinical compute environments, • Drive and enforce a compute-agnostic platform strategy—where data lives in governed storage and multiple engines can query it without creating siloed copies, • Establish and mature dataset contracts, schema governance, and versioning standards that enable domain teams to evolve independently without breaking downstream consumers, • Make and communicate architecture decisions across catalog, ingestion, transformation, and compute, • Establish formal data governance at enterprise scale, including ownership models, access controls, lineage, data quality standards, and compliance frameworks appropriate to healthcare (HIPAA, SOC 2, FedRAMP readiness), • Own the metadata and governance layer, ensuring it is well-adopted across the organization, aligned with the broader catalog strategy, and portable rather than locked to a single vendor, • Drive data quality as an engineering discipline, embedding checks, monitoring, and accountability into platform and domain workflows., • Own the AI/ML infrastructure layer, model training environments, compute provisioning (CPU/GPU), model deployment and serving frameworks, and MLOps tooling, • Ensure the data platform is AI-ready: well-cataloged, semantically rich, and accessible to data science and ML engineering teams across the organization, • Lead and develop the data engineering organization, spanning data platform infrastructure, clinical data engineering, data integration, ML platform, and data operations, • Assess organizational structure and talent against the demands of the platform at scale, making changes where necessary to ensure the right people are in the right roles, • Build a culture of architectural ownership, engineering rigor, and operational accountability, • Represent data platform and AI infrastructure strategy at the executive level, shaping investment priorities and contributing to enterprise technology strategy, • Partner with recruiting to attract and retain senior technical talent in a competitive marketRequirements, • 15+ years in technology leadership, with at least 5 years in a VP or senior director role leading enterprise data platform or data engineering organizations, • Proven track record building and scaling data platforms in complex, high-growth environments, ideally through periods of significant M&A activity, • Deep architectural expertise across the modern data stack: open table formats, cloud data warehouses, streaming infrastructure, transformation frameworks, and metadata/governance tooling, • Experience establishing data governance programs at enterprise scale, including ownership models, data quality frameworks, lineage, and access controls, • Strong understanding of AI/ML infrastructure, model training, serving, MLOps, and how data platform maturity enables AI adoption, • Experience leading in regulated or compliance-heavy environments (healthcare, life sciences, or financial services), • Demonstrated ability to operate as a peer-level leader, credible with engineers, effective with executives, capable of making definitive architectural decisions under ambiguity, • Experience leading geographically distributed engineering teams At Datavant our total rewards strategy powers a high-growth, high-performance, health technology company that rewards our employees for transforming health care through creating industry-defining data logistics products and services. The range posted is for a given job title, which can include multiple levels. Individual rates for the same job title may differ based on their level, responsibilities, skills, and experience for a specific job. The estimated total cash compensation range for this role is:$250,000—$300,000 USD To ensure the safety of patients and staff, many of our clients require post-offer health screenings and proof and/or completion of various vaccinations such as the flu shot, Tdap, COVID-19, etc. Any requests to be exempted from these requirements will be reviewed by Datavant Human Resources and determined on a case-by-case basis. Depending on the state in which you will be working, exemptions may be available on the basis of disability, medical contraindications to the vaccine or any of its components, pregnancy or pregnancy-related medical conditions, and/or religion. This job is not eligible for employment sponsorship. Datavant is committed to a work environment free from job discrimination. We are proud to be an Equal Employment Opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, sex, sexual orientation, gender identity, religion, national origin, disability, veteran status, or other legally protected status. To learn more about our commitment, please review our EEO Commitment Statement here. Know Your Rights, explore the resources available through the EEOC for more information regarding your legal rights and protections. In addition, Datavant does not and will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay. At the end of this application, you will find a set of voluntary demographic questions. If you choose to respond, your answers will be anonymous and will help us identify areas for improvement in our recruitment process. (We can only see aggregate responses, not individual ones. In fact, we aren't even able to see whether you've responded.) Responding is entirely optional and will not affect your application or hiring process in any way. Datavant is committed to working with and providing reasonable accommodations to individuals with physical and mental disabilities. If you need an accommodation while seeking employment, please request it here, by selecting the 'Interview Accommodation Request' category. You will need your requisition ID when submitting your request, you can find instructions for locating it here. Requests for reasonable accommodations will be reviewed on a case-by-case basis. For more information about how we collect and use your data, please review our Privacy Policy.

Job DescriptionNVIDIA AI Infrastructure & Kubernetes Platform Engineer (DGX Systems) Remote NVIDIA Certification required or no interview 6 months to 1+ yrs $open USC or GC req Alternate titles depending on context: • AI Platform Architect DGX & SuperPOD, • AI Infrastructure DevOps Engineer NVIDIA DGX Stack, • Senior AI Systems Engineer DGX | Kubernetes | InfiniBandJob Description: We are seeking a highly skilled AI Infrastructure & Kubernetes Platform Engineer with a proven track record in deploying and managing NVIDIA DGX-based AI clusters, orchestrating containerized AI workloads using Kubernetes, and ensuring secure, high-throughput operations across InfiniBand-powered networks. The ideal candidate will hold a combination of Kubernetes certifications (CKA, CKAD, CKS) and NVIDIA certifications (NCA-AIIO, NCP-AIO, NCP-AII, NCP-AIN), coupled with hands-on training in DGX, BlueField, and high-speed network operations. This position plays a key role in supporting AI/ML infrastructure at scale, enabling efficient training and inference for complex models, and integrating NVIDIA's cutting-edge compute, storage, and fabric solutions with modern DevOps practices. AI Infrastructure Operations • Deploy and manage NVIDIA DGX BasePODs and SuperPODs for high-performance AI workloads., • Oversee DGX system lifecycle operations including provisioning, monitoring, firmware upgrades, and capacity planning., • Operate Base Command Manager to manage GPU clusters, schedule workloads, and integrate with MLOps tools., • Perform DGX node health validation, NCCL interconnect testing, and NVLink topology verification following new deployments or hardware changes.Kubernetes Platform Engineering, • Architect secure and scalable Kubernetes clusters optimized for GPU-accelerated workloads using NVIDIA GPU Operator., • Leverage expertise from CKA/CKAD/CKS to develop, deploy, and secure AI applications on Kubernetes., • Implement CI/CD pipelines and GitOps methodologies for deploying and managing ML workflows.High-Performance Networking & DPUs, • Administer InfiniBand networks and BlueField DPUs using Unified Fabric Manager (UFM)., • Enable NVLink/NVSwitch performance across GPU nodes and tune fabric configurations for minimal latency and maximum throughput., • Use BlueField for offloading storage, firewalling, and telemetry, enhancing AI workload security and performance.Security & Compliance, • Apply best practices from the CKS certification to secure containerized AI environments., • Configure runtime security, secrets management, network segmentation, and auditing using DPU-enhanced Kubernetes deployments., • Support zero-trust architecture initiatives by enforcing workload identity, RBAC policies, and supply chain integrity across AI container images and model artifacts Monitor GPU, CPU, and I/O performance using NVIDIA DCGM, Prometheus, Grafana, and Base Command APIs. • Tune system performance and model training pipelines for cost-efficiency and throughput., • DGX System, BasePOD, and SuperPOD Administration, • BlueField DPU Configuration & Operations, • InfiniBand Fabric and UFM Management, • Base Command Manager for workload orchestration This is a remote position.

Job DescriptionWho We AreQvest US is the global leader in technology and business consulting for the Media & Entertainment and Consumer Packaged Goods & Retail industries. We strategize, advise, design, develop and implement future-forward business & technology solutions. With expertise in digital media supply chain, data & analytics, IP & rights management, broadcast transformation, Salesforce and applied AI, our exceptionally talented teams partner with Fortune 1,000 companies to revolutionize markets and set new industry standards.Who We're Seeking Qvest US is seeking an experienced leader to oversee our US Applied AI practice. You will be responsible for leading the Applied AI practice including strategy, business development, team development and project delivery. This includes leading interactions with customers and channel partners, as well as internal stakeholders to promote the Qvest Applied AI practice and actively participate in the growth of Qvest. The Practice Lead will execute a 2026 GTM (go-to-market), updating as necessary, and create subsequent GTM strategies for the Applied AI practice. They will work closely across Practices, Business Units, and Sales & Marketing to communicate strategy, offerings, and innovation within the Practice, identifying opportunities for new and existing services and solutions that can be offered to clients. The role will also be responsible for working closely with clients in identifying their business needs and providing technical solutions. You will provide operational management on a daily, weekly, and monthly basis to ensure that the Applied AI business is organized and executed so as to positively impact Qvest revenue, retention, growth, and customer satisfaction. Our clients are looking for our expertise to help them build modern AI solutions. We work closely with clients to understand their IT infrastructure, data estate, business objectives, and how Applied AI solutions can help them achieve those objectives. Our industry focus is the Media & Entertainment industry. What You'll Do Business Development and P&L Management * Refine/update a 2026 and beyond go-to-market strategy that resonates with the Media and Entertainment industry and optimizes company growth. * Be accountable for the Applied AI practice revenue and budgets for each year and help create them for following years * Partner with vendors, leadership and sales to identify customer opportunities or identify them using other means. Once identified, understand business objectives and challenges, establish trust and set vision with the customer, develop proposals, and win work for the practice Practice Leadership & Management * Be the face of the practice, develop the practice’s internal and external presence, evangelize and champion our services and products * Articulate the value proposition and ROI of our services and proposed solutions to prospective customers * Stay abreast of industry and technology changes, in the areas of Applied AI technologies, including foundation models and generative AI, especially as they lead us into a world that continues to rapidly move towards AI solutions. * Cultivate and manage the portfolio of offerings, SOWs, and IP to maximize profitability and achieve revenue/margin objectives * Manage the day-to-day operations of the team, including resource allocation, budgeting, and manage a practice-level profit and loss statement, including project management as needed * Contribute to internal growth initiatives including mentorship, recruitment, strategy and/or methodology enhancement Project Delivery * Oversee and ensure accuracy of project plans and estimates during the sales process. * Monitor active projects, ensuring priorities, issues, and risks are appropriately managed. * Follow consulting methodology, lead & advise project teams through all core project phases, including project setup, requirements gathering, design, development, testing, and deployment * Ensure client satisfaction and maintain executive level relationships through consistent support, impactful thought leadership and high-quality project execution. * Understand, develop and articulate complex business challenges into actionable plans with clear and concise communication * Facilitate workshops, provide status updates, and lead meetings across the executive levels of client organizations What You'll Bring * Leadership experience managing teams of functional and technical resources * Hands-on AI expertise and experience including but not limited to: * 8+ years in consulting or AI-focused roles, with experience working across modern machine learning and AI platforms and tools and guiding teams delivering both classical ML and generative AI solutions. * Strong understanding of designing and delivering AI solutions on cloud platforms (AWS, Azure, or GCP), including collaborating with engineering teams, and operational considerations such as scalability, governance, and cost. * Experience leading the delivery of business-driven AI initiatives, translating client business challenges into practical, scalable AI use cases * An understanding of current key AI trends and the AI landscape * Passion for and proven experience with consulting business development * Eagerness to help build and lead a best-in-class Applied AI Practice * Experience with project planning, including tasks, budgeting, resource allocation and balancing * A track record of highly impactful work at prior companies, including both as a manager, a manager of managers, and as an individual contributor. Preferred Experience * Media & entertainment or adjacent industry experience * Knowledge of industry best practices in Applied AI * Experience at a large consulting firm (e.g., Accenture, Deloitte, EY, CapGemini, PWC) * Bachelor’s degree in engineering, computer science, data science, information systems, or a related quantitative field (advanced degree a plus). * Familiarity with established and emerging AI technologies, including foundation models, generative AI, MLOps tooling, model governance, and responsible AI practices. Travel RequirementsEmployees are responsible for traveling to and from client sites as required by their project or assignment, regardless of location. Travel may include sites outside the employee’s primary office location, state, or region. Remote & Hybrid WorkWhile remote or hybrid work may be permitted for certain projects, client needs take precedence. Employees are expected to report onsite at the client location when required by the project scope, client request, or management directive. Life at QvestWe were founded on a culture of collaboration and inclusiveness, and this permeates each of our initiatives, both client-facing and internal. We offer a wide selection of benefits including medical, dental & vision, 401k matching and flexible vacation; we sponsor training to advance our teams’ skill sets and we prioritize our employees’ professional growth paths. Qvest US is currently 300+ people strong and we’ve been recognized as a “Best Place to Work,” a “Great Place to Work,” “Fastest Growing,” and “A Jewel." Equal Employment OpportunityQvest is an Equal Opportunity 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 other characteristic protected by law. Qvest applies this stance to all employment actions, including but not limited to recruitment, hiring, upgrading, promotion, transfer, demotion, layoff, recall, termination, rates of pay or other forms of compensation and selection for training, including internships, at all levels of employment.

Job Description Founded in 2012, H2O.ai is on a mission to democratize AI. As the world’s leading agentic AI company, H2O.ai converges Generative and Predictive AI to help enterprises and public sector agencies develop purpose-built GenAI applications on their private data. With a focus on Sovereign AI—secure, compliant, and infrastructure-flexible deployments—H2O.ai delivers solutions that align with the highest standards of data privacy and control. Our open-source technology is trusted by over 20,000 organizations worldwide, including more than half of the Fortune 500. H2O.ai powers AI transformation for companies like AT&T, Commonwealth Bank of Australia, Chipotle, Workday, Progressive Insurance, and NIH. H2O.ai partners include NVIDIA, Dell Technologies, Deloitte, Ernst & Young (EY), Snowflake, AWS, Google Cloud Platform (GCP), VAST Data and MinIO. H2O.ai’s AI for Good program supports nonprofit groups, foundations, and communities in advancing education, healthcare, and environmental conservation. With a vibrant community of 2 million data scientists worldwide, H2O.ai aims to co-create valuable AI applications for all users. H2O.ai has raised 256 million from investors, including Commonwealth Bank, NVIDIA, Goldman Sachs, Wells Fargo, Capital One, Nexus Ventures and New York Life. For more information, visit . About This Opportunity We are looking for a Senior Sales Engineer - AI to join our team. In this role, you’ll combine deep technical expertise in Machine Learning and Generative AI with strong pre-sales solutioning skills to help enterprise customers design, adopt, and scale AI using the H2O.ai platform. You’ll work hand-in-hand with Sales, Product, and Customers - leading technical discovery, designing architectures, running demos and pilots, and guiding customers through their end-to-end AI journey. This position is based in New York. What You Will Do • Partner with Sales to drive pre-sales success: lead discovery sessions, identify customer needs, design technical solutions, and build winning proposals., • Execute high-impact proof of value that moves beyond technical feasibility to demonstrate ROI, such as cost per token or measurable accuracy gains in production using H2O AI Enterprise Platform: Predictive, Generative, and Agentic AI, • Build and present custom AI/ML/GenAI solutions tailored to industry verticals (banking, finance, insurance, healthcare, manufacturing, retail, public sector)., • Showcase hands-on expertise with LLMs: fine-tuning, evaluations, RAG, and Agentic pipelines., • Design and build sophisticated Agentic Workflows, beyond simple RAG to multi-agent systems that can reason, use tools, and execute complex business logic autonomously., • Design reference architectures and deployment strategies for enterprise customers across cloud (AWS, Azure, GCP), hybrid, and on-prem., • Architect integrated solutions that leverage the full H2O stack: using Driverless AI for predictive features, h2oGPTE for unstructured data synthesis, • Guide customers on MLOps, Kubernetes deployments, CI/CD integration, monitoring, and governance to ensure their applications are production-ready., • Work closely with Product Management to influence the product roadmap based on customer and field insights., • Contribute to thought leadership by creating solution blueprints, best practices, and reusable assets; represent H2O.ai at events, roundtables, webinars, and conferences.What We Are Looking For, • 5+ years in pre-sales, sales engineering, or solution architecture roles for enterprise AI/ML platforms., • Hands-on expertise in Generative AI and ML: LLM fine-tuning, evaluation, pipelines, predictive ML algorithms., • Proven experience with cloud-native deployments (AWS, Azure, GCP), Kubernetes, and enterprise integration., • Master the art of technical storytelling, the ability to whiteboard a complex Kubernetes deployment for an IT Director, then pivot to explaining the risk-mitigation benefits of 'Guardrails' to a Chief Risk Officer., • Excellent presentation and communication skills: confident in front of C-level executives and technical teams., • Experience with H2O.ai products or similar enterprise AI/ML platforms is a plus., • Willingness to travel up to 50% to support strategic accounts.How to Stand Out, • Experience running POCs, pilots, and executive workshops that accelerate AI adoption., • Familiarity with enterprise security, compliance, and governance in AI deployments., • Demonstrated thought leadership (talks, blogs, open-source contributions)., • Market leader in total rewards, • Remote-friendly culture, • Flexible working environment, • Be part of a world-class team H2O.ai is an innovative AI cloud platform company, leading the mission to democratize AI for everyone. Thousands of organizations from all over the world have used our cutting-edge technology across a variety of industries. We’ve made it easy for people at all levels to generate breakthrough solutions to complex business problems and advance the discovery of new ideas and revenue streams. We push the boundaries of what is possible with artificial intelligence. H2O.ai employs the world’s top Kaggle Grandmasters, the community of best-in-the-world machine learning practitioners and data scientists. A strong AI for Good ethos and responsible AI drive the company’s purpose. Please visit to learn more. #LI-Hybrid Powered by JazzHR e0ReZA0xCQ

Job DescriptionCompany Description Strategy (Nasdaq: MSTR) is at the forefront of transforming organizations into intelligent enterprises through data-driven innovation. We don't just follow trends—we set them and drive change. As a market leader in enterprise analytics and AI software, we've pioneered the BI and analytics space, empowering people to make better decisions and revolutionizing how businesses operate. We are now also at the forefront of AI disruption, providing data via our enterprise semantic layer to AI agents, tools, and platforms. But that's not all. Strategy is also leading a groundbreaking shift in digital assets, adopting bitcoin as our primary treasury reserve asset in 2020. Since then, we have issued innovative bitcoin-backed securities and have been the leader in bitcoin treasury companies. This visionary move has helped us build a fortress balance sheet, and is solidifying our position as a forward-thinking, innovative force in the market. Our people are the core of our success. At Strategy, you'll join a team of smart, creative minds working on dynamic projects with cutting-edge technologies. We thrive on curiosity, innovation, and a relentless pursuit of excellence. Our corporate values—bold, agile, engaged, impactful, and united—are the foundation of our culture. As we lead the charge into the new era of AI and financial innovation, we foster an environment where every employee's contributions are recognized and valued. Join us and be part of an organization that lives and breathes innovation every day. At Strategy, you're not just another employee, you're a crucial part of a mission to push the boundaries of analytics and redefine financial investment.Job Description Role Overview As a Customer Success Manager (CSM) at Strategy, you will serve as the primary bridge between our enterprise customers and Strategy's engineering, product, and go-to-market teams. You will own the full post sales lifecycle of a customer account portfolio, ensuring customers do not simply "use" the platform but deeply integrate Strategy's cloud-native architecture, Semantic Layer (Mosaic), and AI-powered analytics capabilities into their core technology stack. Your goal is to drive measurable business value and Net Revenue Retention (NRR) by ensuring the platform is technically optimized, strategically adopted, and commercially positioned to expand. Location: New York, NY. Candidates must reside in the New York metropolitan area (NY, NJ, PA, RI, or CT) and be able to commute to the New York's office as needed. Key Responsibilities 1. Technical Strategy & Customer Success * Act as the lead technical advisor for your accounts, guiding customers through complex cloud-native architectures, Semantic Layer (Mosaic) implementations, and AI-driven analytics workflows. * Leading C-suite whiteboard sessions to align platform capabilities with high-level business goals. * Deep-diving into client workflows to uncover and implement high-value use cases. * Translate executive requirements into value realization plans, ensuring technical migrations and data initiatives result in realized ROI and account growth. * Develop and execute customer roadmaps that align with enterprise architecture, security requirements, and strategic business objectives — defining measurable KPIs and adoption milestones. * Lead Quarterly Business Reviews (QBRs) with both business and technical stakeholders, demonstrating ROI, reviewing progress against success metrics, and aligning on future priorities. 2. Technical Enablement & Adoption * Lead the technical configuration and integration phase to accelerate time-to-value, partnering with implementation teams to ensure a smooth transition from deployment to operational use. * Conduct deep-dive technical demonstrations, developer "Office Hours," and capability workshops for engineering, data science, and BI teams. * Proactively monitor account health using technical telemetry — identifying and resolving performance bottlenecks, integration inefficiencies, and adoption gaps before they impact customer satisfaction. * Monitor customer health, engagement trends, and platform adoption data to proactively identify risks and opportunities for value expansion across the account. 3. Product Advocacy & Engineering Collaboration * Synthesize technical feedback and edge cases from the field to influence Strategy's Product and Engineering roadmaps, acting as the customer's internal advocate. * Partner with Engineering to lead strategic customers through Alpha/Beta programs for new AI, Mosaic, and platform features. * Serve as a high-level technical point of contact for complex support escalations, coordinating between the customer's engineering team and Strategy's internal developers to drive timely resolution. * Advise customers on platform enhancements, integrations, and upgrades — ensuring alignment with the Strategy product roadmap and the customer's long-term data strategy. 4. Commercial Collaboration & Customer Advocacy * Support the successful renewal and expansion of customer accounts by ensuring continuous technical and business value realization from the Strategy platform. * Partner with Sales and Account Management to identify upsell and cross-sell opportunities, providing account health insights and adoption data that inform commercial strategy. * Proactively identify renewal risks and collaborate with Sales and leadership on mitigation plans before they escalate. * Develop strong referenceable customers willing to participate in case studies, testimonials, reference calls, and industry events. Qualifications Core Technical Requirements * Bachelor’s degree in business administration, Computer Science, Engineering, Data Science, or a related discipline (or equivalent practical experience) required. * Hands-on experience with cloud-native services (microservices, Kubernetes, Docker) and major cloud providers (AWS, Azure, or GCP). A professional cloud certification is strongly preferred. * Strong understanding of data modeling, ETL/ELT processes, semantic layers, and the lifecycle of Machine Learning models (MLOps and AI deployment). * Familiarity with enterprise analytics, Business Intelligence tools, or AI-driven data platforms is highly desirable. Experience & Professional Skills * 7+ years of experience in a customer-facing Customer Success role — such as Customer Success Manager, Technical Account Manager, Solutions Architect, Sales Engineer, or Technical Consulting — within a SaaS or enterprise software environment. * Demonstrated experience managing strategic or enterprise customer accounts across complex, multi-stakeholder organizations. * Ability to analyze usage data and platform telemetry to identify patterns, surface insights, and deliver data-driven recommendations for expansion and optimization. * Exceptional ability to explain complex technical concepts (e.g., universal semantic layers, data fabric, cloud-native architecture) clearly to non-technical executive stakeholders. * Strong project management and collaboration skills, with experience working across Sales, Product, Engineering, and Support functions. * Familiarity with Agile development cycles and DevOps practices to support customer engineering teams effectively. * Experience with CRM and customer success tools such as Salesforce, Gainsight, or equivalent platforms. Additional Information Strategy is an equal opportunity employer. All applicants will receive consideration for employment without regard to race, creed, color, religion, national origin, gender, sex, sexual orientation, gender identity, disability, veteran status, age, genetic information, or any other legally-protected basis. Strategy provides reasonable accommodation for qualified individuals with disabilities in the hiring process. If you have any difficulty using our online system and you need an accommodation due to a disability, you may contact us about your interest in employment at . Visit Strategy’s Careers page for additional information.

Logic20/20 is seeking a Senior MLOps Engineer to support data science teams utilizing artificial intelligence and machine learning to predict and analyze computer vision or customer intent models. MLOps), data, and/or software engineer using Python in a production environment.

Outlier helps the world’s most innovative companies improve their AI agents by providing human feedback.We collaborate with leading AI organizations to train Large Language Models (LLMs) to function as proactive, multi-step agents.Our projects focus on teaching these systems how to design, coordin

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A leading healthcare solutions provider in the United States seeks an ML Engineer passionate about MLOps and data reliability.

Responsibilities include overseeing ML data foundations, implementing MLOps practices, and collaborating across organizations to meet business needs.

Key Responsibilities Professionals in this role may contribute to: Machine Learning Model Development Review Review machine learning scenarios involving model development, training workflows, feature engineering, evaluation metrics, and model behavior Evaluate ML outputs against source materials, te

We're seeking talented MLOps Engineers with deep, hands-on expertise in modern ML frameworks — specifically JAX, PyTorch, and kernel-level programming (Pallas/Triton). Key Responsibilities - Guide research and engineering teams to close knowledge gaps and improve AI model performance in MLOps, tra

Key Responsibilities Professionals in this role may contribute to: Machine Learning Model Development Review Review machine learning scenarios involving model development, training workflows, feature engineering, evaluation metrics, and model behavior Evaluate ML outputs against source materials, te

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The role will apply statistical programming, modeling, visualization techniques, data mining, and forecasting skills to analyze challenging public sector problems.Analytica has been recognized by Inc.We offer competitive compensation with opportunities for bonuses, employer paid health care, trainin

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Sleeper is a sports-focused games platform with messaging at its core.We are a young and energetic company, fueled by a passion for sports and a drive for innovation.Our mission is to create a digital playground for sports fans and their friends to hang out.We bring people together over sports.At Sl

Reports to: Head of Data Science.Location: Remote, but we will be strongly weighting applicants who are in or willing to move to Austin.Applications will be open through early April with an anticipated start date of April 20, 2026.Funga is a public benefit corporation harnessing forest fungal networ