1,301 to 1,325 of 1,438 Permanent Machine Learning Jobs

APN Consulting, Inc. is a progressive IT staffing and services company offering innovative business solutions to improve client business outcomes. We focus on high impact technology solutions in ServiceNow, Fullstack, Cloud & Data, and AI/ ...

physical robot hardware Mentor junior researchers and engineers, and publish at top-tier venues What We're Looking For Essential: PhD/MSc in ML, Robotics, CS, or related field with 4+ years of equivalent industry research experience Demonstrated expertise training and deploying learned manipulation policies on real robots Strong … tier venues — conference attendance and open-source contributions are actively supported What's On Offer Join a team with world class applied research scientists, ML engineers, and robotics software engineers A mature platform that ships to physical hardware, not slides Active support for conference attendance and open-source contributions Competitive ...

small London startup with the ambition to change education with ML-powered tutoring. Our flagship product is a mobile application for teaching English to intermediate and advanced learners. We’re on the verge of solving one of the biggest challenges in education – making high-quality, personalised learning accessible … system for millions of users Build convenient CI/CD processes and testing pipelines to support quick iterative development and system stability Work on ML model development with our team to build robust data pipelines and deploy ML models Analyse large corpora of data and build real-time recommendation systems ...

quality training programs focused on Starburst, Dell Data Lakes, and Data Warehousing architectures. · Create engaging, hands-on materials such as labs, case studies, presentations, learning content that support enterprise data analytics adoption. Inline with directives given by line manager · Ensure training material is tailored to a wide range … both technical and nontechnical users ideally within a software vendor, data platform provider, or cloud services organization. · Strong knowledge of data engineering, AI/ML fundamentals, and data platform architecture. · Experience with or exposure to Starburst, Dell Data Lakes, and Data Warehousing technologies (e.g., Snowflake, Redshift, BigQuery). · Excellent communication ...

/LangChain, Knowledge management using RAGs/GraphRAGs, Vector Databases Building multi agent solutions, complex Agentic workflows Evaluate and optimize Agent output & performance Traditional ML - model selection, model performance evaluation/monitoring Ability to interact with business teams and convert business needs to AI/ML workflows - Must demonstrate … agent systems Qualifications Education: A B.S. or M.S. in Computer Science, AI, or a related field is preferred. Experience: 4+ years in AI/ML engineering are preferred, with 1+ years specifically focused on agentic AI or GenAI applications. Responsibilities Collaborate closely with the team to rapidly gather requirements from ...

Consumer Marketplace/App Department: Product & Insights A leading global marketplace is hiring a Senior Product Analyst to partner with product, engineering, design, and ML teams to shape the future of a mobile-first product used worldwide. What You'll Do Act as the lead data scientist for a core … interpret experiments across the product ecosystem Influence product strategy by connecting insights to business goals Improve datasets, dashboards, and analytical tooling Work closely with ML teams on discovery, ranking, and personalisation initiatives What We're Looking For Expert-level SQL + solid Python for product analytics Hands-on A/ ...

build reproducible training and evaluation data pipelines. - Track what frontier labs are shipping and bring back what's relevant. ## Essential experience - Experience building ML/AI systems in a research-adjacent context (industry, lab, or PhD). - Experience building LLM-powered systems: prompts, context engineering, agent architectures. - Experience working … model training generally, including the data, optimisation, and evaluation work around it. - Strong engineering fundamentals. Fluent in Python and comfortable across the AI/ML stack. - Experience running experiments rigorously, in academia or industry. You think about confounds. You can defend your results. - Experience with training and evaluation data pipelines ...

build reproducible training and evaluation data pipelines Track what frontier labs are shipping and bring back what's relevant Essential experience Experience building ML/AI systems in a research-adjacent context, industry, lab, or PhD Experience building LLM-powered systems: prompts, context engineering, agent architectures Experience with evaluations … with model training, including the data, optimisation, and evaluation work around it Strong engineering fundamentals, fluent in Python and comfortable across the AI/ML stack Rigorous approach to experiments: you think about confounds and can defend your results Experience with training and evaluation data pipelines, including reproducibility and observability ...

implementations and innovation -Communicate GenAI potential and technical challenges to engineering teams and C-Level executives, leveraging expertise in GPU based compute infrastructure and ML frameworks -Identify cross-industry patterns and trends to accelerate innovation and represent best practices to customers and partners Working with diverse teams across the organization … within short lead times and with minimum of waste. Work to develop and maintain a highly automated Continuous Delivery pipeline. Your skills and experience ML and using GenAI to solve problems Good experience in Python, NodeJS, ReactJS, Java Agentic Framework experience is an added advantage Experience using LLMs, ML algorithms ...

This role sits within a major UK Defence digital transformation programme, driving the design, build and demonstration of AI/ML proof-of-concepts across sensitive mission data, legacy estates and modern cloud platforms. The environment is heavily aligned to Oracle technologies, so experience with Oracle’s cloud-native … stack is strongly desired (but not essential). Key Responsibilities/Experience • Design, prototype and deliver AI/ML PoCs (RAG pipelines, LLM-powered services, agent-based automation, generative use cases) aligned to Defence workflows and mission needs. • Build high-performance backend components to support AI workloads, including retrieval layers ...

in a fast-paced R&D environment Excellent communication skills to articulate technical issues and blockers clearly Desirable Skills: Experience with AI/ML tools, LLMs, speech services, RAG systems, or AI APIs Experience with Unreal Engine, Unity, or other real-time 3D development environments Familiarity with Docker, FastAPI ...

stack engineer, Python/Java developer, DevOps/cloud engineer, plus data-track roles like data analyst, BI analyst, data engineer, data scientist, and ML/AI engineer. The focus areas remain: Java/Full Stack/DevOps and Data Analytics/Data Engineering/Data Science/ML/ ...

stack engineer, Python/Java developer, DevOps/cloud engineer, plus data-track roles like data analyst, BI analyst, data engineer, data scientist, and ML/AI engineer. The focus areas remain: Java/Full Stack/DevOps and Data Analytics/Data Engineering/Data Science/ML/ ...

technical discipline Technical knowledge in data centers design and construction, specifically POD-level architecture and modular design, high-density compute environments (AI/ML workloads) and/or liquid cooling architectures Project Management Experience: Experience with Product Design or Product Management with a working knowledge of Agile/Scrum … edge DMAIC experience for process improvement and drive for excellence Experience delivering POD-level architecture and modular design High-density compute environments (AI/ML workloads) and cross-domain system integration (cooling, power, structural) Proven ability to author whitepapers and thought leadership and lead system-level design trade-off discussions ...

roles, or AI-focused innovation. Knowledge of one or more key industries: A&D, Finance, Healthcare, Government, or Life Sciences. Familiarity with AI/ML frameworks, Data platforms, and Cloud ecosystems (Azure, AWS, GCP). Ability to translate complex technical concepts into clear business value. Strong communication and stakeholder engagement … emerging AI technologies. Opportunity to shape the future of AI adoptionwithin some of the UKs most impactful industries. Collaborative, forward-thinking environment with continuous learning and development opportunities. ...

creatives, strategists, and studio teams to understand workflows and pain points. Translate needs into user stories, functional specs, and prioritized backlogs. Work closely with ML engineers, platform developers, and integration architects to refine requirements. Ensure features support both production scalability and creative quality. Product Delivery & Release Management Own sprint planning … . Strong understanding of advertising and content operations workflows—especially versioning, localization, and high-volume creative production. Experience working with cross-functional engineering teams (ML, platform, DevOps). Clear communication skills with the ability to translate technical capability into business value. Preferred Experience within WPP, WPP Production, or large agency ...

platforms integrate with Microsoft Dynamics 365 and Dataverse, prior experience isn't required - we're happy to support the right developer in learning these technologies over time. This is a great opportunity for someone who enjoys backend engineering, APIs, cloud services, automation, and solving real-world technical problems … Vault Exposure to Microsoft Dynamics 365 or Dataverse SQL and relational database experience JavaScript or TypeScript knowledge Interest in AI/ML concepts, LLMs, OCR, or workflow automation Experience with Power Platform (Power Apps/Power Automate) What We Offer Remote-first working environment Salary up to £55,000 depending ...

WOULD BE GREAT IF YOU ALSO HAD Experience with Databricks or Snowflake, particularly in analytical or data-intensive contexts Familiarity with AI/ML in production: model serving, prompt pipelines, or agentic patterns Experience with consumption-based and subscription billing Experience with self-serve billing platform integrations Exposure to aviation … during your birthday month ⚡ Octopus EV salary sacrifice scheme 🌍 Work remotely anywhere in the world for up to 1 month per year 📚 Annual learning and development budget. OAG is committed to creating an inclusive workplace where everyone feels valued and able to perform at their best. We welcome applications ...

reporting and insight transformation initiatives • Partner with senior stakeholders to identify and prioritise high-value opportunities • Guide development of predictive models , forecasting tools and ML-driven solutions • Collaborate with Product, Engineering and Governance teams to deliver measurable business impact • Build a culture of experimentation, innovation and continuous improvement Key Details … Central London • Team: Direct responsibility for Analytics and Data Science leadership, managing c.14 specialists • Tech Environment: SQL, Python, R, AWS, Snowflake, Tableau, Analytics & ML platforms • Visa Sponsorship: May be considered for exceptional candidates Interested? Please apply below. ...

contribute to peer code reviews You'll need to have Strong Python engineering skills (clean, modular, production-ready code) Experience in data science, including ML/statistical modelling for MMM and econometrics Strong SQL for data extraction and analysis Solid understanding of software engineering fundamentals (Git, agile workflows) Ability … contribute to peer code reviews You'll need to have Strong Python engineering skills (clean, modular, production-ready code) Experience in data science, including ML/statistical modelling for MMM and econometrics Strong SQL for data extraction and analysis Solid understanding of software engineering fundamentals (Git, agile workflows) Ability ...

across triage, pricing, defect detection, compliance verification, fraud analytics, and claims modeling. In this role you will: Build, train, and iterate CLIENT's core ML models: pBad triage, hazard-based risk pricing, and defect detection modules covering appraisal, income recalculation, and ATR compliance Build and maintain the servicer compliance verification … loan data Basic Qualifications: 6+ years of quantitative modeling with at least 3 years in mortgage credit risk, structured finance, or specialty insurance Supervised ML models built, deployed, and reviewed by external auditors Strong Python with scikit-learn, XGBoost, or PyTorch Preferred Qualifications: Non-QM mortgage underwriting, defect taxonomy ...

settle in, you'll take on more of the wider people work recruitment, performance, identifying where the team needs to grow in AI/ML and SRE. We'll support you to learn this side of the role; we don't expect you to arrive with it fully formed. … apply. Your application will be even stronger if you can also demonstrate the following desirable criteria: Hands-on exposure to AI/ML in production systems Experience helping establish SRE or observability practice early on A track record of modernising legacy systems without breaking them What this role offers someone ...

.NET Developer, C# 14 - Financial Consultancy - London (Tech stack: .NET Developer, .NET 10.0, ASP.NET Core, C# 14, .NET MAUI, ML.NET, Azure AI, GitHub Copilot, Docker, Kubernetes, .NET Aspire, CI/CD, HTML Living Standard, CSS ...

signals into actionable compound discovery and optimisation, powering a pipeline across: Discovery → Prediction → Design → Validation We are looking for a Senior Computational Biologist with ML Engineering background to help build, bridge, and functionalise the link between AI-powered biological discovery and real-world clinical outcomes. This role sits across biological … discovery and scalable ML engineering. You will own key parts of the end-to-end architecture from data to model to evaluation to deployment, and work closely with ML engineers and software engineers to productise the platform into client-ready outputs. This is a senior role with significant autonomy ...

/ML Engineer (Chandler, AZ): Design, build, and deploy end-to-end AI/ML systems spanning model research, engineering, and productionization. Architect and establish standards for the full ML lifecycle. Develop and fine tune LLMs and transfer based models (BERT, Longformer, Mixtral)for tasks such as NER, structured data ...