51 to 75 of 3,210 Machine Learning Jobs in London

Engineering function responsible for designing, building and scaling enterprise-grade AI platforms. This is an exciting opportunity to work on cutting-edge Artificial Intelligence, Machine Learning and Large Language Model (LLM) initiatives, helping to transform innovative AI research into secure, scalable production systems. The role is open … maintain scalable AI data pipelines and processing workflows. Architect cloud-native backend systems and distributed AI services. Collaborate closely with Data Scientists to productionise Machine Learning and NLP models. Develop high-performance RESTful APIs and microservices for AI model serving. Drive system reliability, monitoring, observability and performance optimisation. ...

Applied Innovation (of AI) Engineering team is an elite machine learning group strategically located within the Chief Data Analytics Office (CDAO) Technology group of JP Morgan Chase. AI Engineering tackle business critical priorities using innovative machine learning techniques and technologies with a focus on machine learning for Software, Cybersecurity and Technology Infrastructure. The team partners closely with all lines of business and engineering teams across the firm to execute long-term projects in these areas that require significant machine learning development to support JPMC businesses as they grow. As a Principal ...

apprenticeship, coaching, and exposure that will accelerate your growth in ways you won’t find anywhere else.When you join us, you will have:Continuous learning: Our learning and apprenticeship culture, backed by structured programs, is all about helping you grow while creating an environment where feedback is clear … actionable, and focused on your development. The real magic happens when you take the input from others to heart and embrace the fast-paced learning experience, owning your journey.A voice that matters: From day one, we value your ideas and contributions. You’ll make a tangible impact by offering ...

Markets Operations workflows, controls, exception management, and productivity use casesDefine and drive AI engineering architecture patterns for scalable, secure, reusable, and production-ready AI, machine learning, and generative AI solutionsDesign and implement agent harnesses, orchestration layers, tool-use frameworks, workflow automation patterns, and guardrails for enterprise AI applicationsDevelop … monitoring, and feedback mechanisms for AI systems, including quality measurement, hallucination reduction, regression testing, model performance tracking, and operational risk controlsDesign approaches for continual learning and improvement, including human-in-the-loop feedback, telemetry-driven enhancement, model, prompt, and version management, and safe release practicesCollaborate with Markets Operations stakeholders ...

Time Analyst in the Data & AI Program at JPMorganChase, you will drive impact by building end-to-end data, analytics, and artificial intelligence and machine learning solutions that translate business objectives into measurable outcomes for clients and customers. Working alongside global experts in collaborative teams, you will design … encourage you to submit your application as early as possible before job postings close. Job ResponsibilitiesBuild intelligent systems that power real business outcomes, from machine learning models to generative artificial intelligence and agent-based solutions.Work hands-on with cutting-edge technologies to design, develop, and deploy artificial intelligence ...

Client Engagement & DeliveryData Pipeline Development (Batch and Streaming)Snowflake & Cloud Data PlatformsData Architecture & ModellingCollaboration & Best PracticesQuality, Governance & Security Business Relationships: Solution ArchitectsData Engineers, Developers, ML Engineers and AnalystsClient stakeholders up to Head of Data Engineering, Chief Data Architect, and Analytics leadership What experience you'll bring: Competencies/Critical Skills … Spark, Hadoop).Experience with version control tools (GitHub, Bitbucket) and CI/CD pipelines.Understanding of data governance, security, and compliance frameworks.Exposure to AI/ML workloads desirable. Experience, Qualifications, and Education: Experience: Minimum 5–8 years in data engineering, data warehousing, or data architecture roles, with at least 3+ years ...

iterate and improve AI capabilities based on user feedback and performance data.What You'll Bring- 5+ years of hands-on experience in AI/ML engineering, software development, or related technical roles with demonstrable experience building and deploying AI-powered applications- Good theoretical knowledge of AI, ML and NLP principles … from OpenAI, Anthropic, etc.Demonstrated proficiency in prompt engineering and orchestrating AI agents, chatbots, and autonomous workflowsCloud, Deployment & Operations Experience- Familiarity with cloud AI/ML services (Azure preferred, also AWS or Google Cloud), container orchestration (Docker, Kubernetes), CI/CD deployment pipelines, automated testing for LLM applications, infrastructure monitoring, logging ...

Senior AI Engineer (Senior/Principal Consultant) to join our Technology Delivery team. In this role, you’ll combine deep expertise in AI/ML engineering and software development to design, build, and deploy advanced generative AI and agentic systems for leading financial services clients. You’ll work hands … responsible AI practicesWhy Join CapcoDeliver high-impact technology solutions for Tier 1 financial institutionsWork in a collaborative, flat, and entrepreneurial consulting cultureAccess continuous learning, training, and industry certificationsBe part of a team shaping the future of digital financial servicesHelp shape the future of digital transformation across FS & EnergyBenefitsWe offer ...

Science, or a related technical field. Professional Experience: Relevant experience across product development, data and AI, with a significant portion focused on AI/ML-driven products and heavy exposure in recent years to Generative AI. Technical Expertise: Experience with Python, SQL and production analytics workflows; familiarity with big-data … build, and scale complex software systems, including experience with cloud architectures, distributed systems, and modern software development practices. Proven experience in architecting AI/ML solutions with a strong understanding of how to integrate with existing enterprise platforms. Domain Knowledge: Strong experience within the Capital Markets domain is highly preferred. ...

Data Science, or a related technical field.Professional Experience: Relevant experience across product development, data and AI, with a significant portion focused on AI/ML-driven products and heavy exposure in recent years to Generative AI.Technical Expertise: Experience with Python, SQL and production analytics workflows; familiarity with big-data platforms … build, and scale complex software systems, including experience with cloud architectures, distributed systems, and modern software development practices. Proven experience in architecting AI/ML solutions with a strong understanding of how to integrate with existing enterprise platforms.Domain Knowledge: Strong experience within the Capital Markets domain is highly preferred. Specific ...

experience in building or evaluating Generative AI models Experience in program/project management and team leadership Strong programming skills in Python and deep learning frameworks (PyTorch, TensorFlow) Demonstrable knowledge of Responsible AI issues, trends, frameworks, and best practices Working knowledge of emerging AI regulatory and legal frameworks across … background in empirical evaluation, experimental design, or benchmarking Deep familiarity with software engineering workflows and developer tools Experience working with or evaluating AI/ML models, preferably LLMs Strong analytical and communication skills, including the ability to write clear testing result reports Nice-to-have experience: Experience with quantitative social ...

into enterprise systems via APIs and data pipelines, with strong security, data governance and residency practices.Cloud: AWS, Azure or GCP, including managed AI/ML services.Delivery: Agile, CI/CD, modern SDLC and TDD.Data and architecture: Modelling across relational, columnar and vector stores, grounded in sound architectural principles.Ways of working … publishing heritage, we combine quality information and vast data sets with analytics to support visionary science and research, health education, and interactive learning, as well as exceptional healthcare and clinical practice. At Elsevier, your work contributes to the world’s grand challenges and a more sustainable future. We harness ...

opinions, loosely held. You can articulate your technical vision and bring others along with you, but you're also open to being wrong and learning from your peers. A focus on impact. You understand that our goal is to deliver value to users and make Assist better every day. … grow. You see mentoring and knowledge-sharing as part of your role. Bonus points Direct experience building evaluation or testing frameworks for AI/ML systems Experience with LLM evaluation techniques, prompt engineering, or AI safety concepts Experience with data pipeline tools like Apache Airflow, Dagster, or similar Experience with ...

opinions, loosely held. You can articulate your technical vision and bring others along with you, but you're also open to being wrong and learning from your peers.A focus on impact. You understand that our goal is to deliver value to users and make Assist better every day. … them grow. You see mentoring and knowledge-sharing as part of your role.Bonus points forDirect experience building evaluation or testing frameworks for AI/ML systemsExperience with LLM evaluation techniques, prompt engineering, or AI safety conceptsExperience with data pipeline tools like Apache Airflow, Dagster, or similarExperience with analytics platforms, experimentation ...

development — prompt engineering, fine-tuning, RAG pipelines, context window managementAgentic AI frameworks — LangChain, LangGraph, AutoGen, or similar; building multi-step autonomous workflowsMachine Learning — model … development, training, evaluation, and deploymentAPIs & backend development — FastAPI, REST APIs, microservices architectureVector databases & embeddingsCloud platforms — Azure GCP, or AWS; deploying and managing AI/ML workloads at scaleVersion control & MLOps — Git, CI/CD pipelines, model versioning, monitoring in productionData handlingRequired — Experience & MindsetDemonstrated end-to-end delivery: problem build deployed ...

projects over the full lifecycle, from conception to data preparation, model engineering, evaluation and deployment and finally model monitoring and maintenanceEstablishing and developing ML Ops frameworks and standards for clients and embedding within their infrastructureWorking with clients to take them on the journey, upskilling along the way and ensuring … loop and can take ownership after you roll off the projectPerforming maturity assessments across clients’ Cloud/AI environments and recommending improvementsBuilding ML strategy blueprints and advising clients on the different technology optionsTranslating business requirements (both functional and non-functional) into solutions, ensuring compliance with the organisations strategy, policies ...

Pipeline Development (Batch and Streaming)• Snowflake & Cloud Data Platforms• Data Architecture & Modelling• Collaboration & Best Practices• Quality, Governance & SecurityBusiness Relationships• Solution Architects• Data Engineers, Developers, ML Engineers and Analysts• Client stakeholders up to Head of Data Engineering, Chief Data Architect, and Analytics leadershipTo thrive in this role, you need to have … Experience with version control tools (GitHub, Bitbucket) and CI/CD pipelines.• Understanding of data governance, security, and compliance frameworks.• Exposure to AI/ML workloads desirable. Experience, Qualifications, and Education• Experience: Minimum 5–8 years in data engineering, data warehousing, or data architecture roles, with at least 3+ years ...

Streaming)• Databricks & Lakehouse Architectures• Data Modelling & Optimisation (Delta Lake, Medallion architecture)• Collaboration & Best Practices• Quality, Governance & SecurityBusiness Relationships• Solution Architects• Data Engineers, Developers, ML Engineers, and Analysts• Client stakeholders up to Head of Data Engineering, Chief Data Architect, and Analytics leadershipTo thrive in this role, you need to have … Experience with version control tools (GitHub, Bitbucket) and CI/CD pipelines.• Understanding of data governance, security, and compliance frameworks.• Exposure to AI/ML workloads desirable. Experience, Qualifications, and Education• Experience: Minimum 5–8 years in data engineering, data warehousing, or data architecture roles, with at least 3+ years ...

developing teams, supporting capability growth through mentoring, coaching and creating a collaborative, high performing environmentExperience Required:·Strong Python and SQL experience·Applied AI engineering, ML engineering or software engineering background·Experience with LLMs, RAG, embeddings, prompt engineering or fine tuning·Exposure to LangChain, LangGraph, Agent Development Kit or similar agent ...

fantastic team of technology experts. You will be responsible for designing, developing, and maintaining data pipelines and systems that enable data analysis and machine learning. You will also collaborate with data scientists, analysts, and other stakeholders to ensure data quality and reliability. Key Responsibilities: Develop Data Engineering solutions ...

reliability, latency, and business outcomes. Qualifications and experience we consider to be essential for the role: 10–15 years across software engineering, AI/ML, data science, or enterprise architecture, with a clear trajectory into senior technical leadership. Proven track record architecting and deploying production-scale AI, from strategy through ...

investment banking environments Strong communication and stakeholder management skills Willingness to work in a hybrid model based in London, UK Exposure to AI/ML-powered tooling in software engineering or DevOps workflows Experience integrating automation or AI tools into CI/CD pipelines or developer workflows Career Stage Senior ...

cost controls built in.Build platforms that support rapid experimentation while meeting production standards for latency, scale, monitoring, SLOs, playbooks, and operational excellence.Partner closely with ML engineers, product engineers, data scientists, and platform teams across DoorDash, Wolt, and Deliveroo to turn emerging GenAI capabilities into durable platform primitives.Shape the future … equivalent3+ years of industry experience in software engineeringStrong backend engineering fundamentals, especially in Python and distributed systems.Experience building production services, APIs, data pipelines, or ML infrastructure at scale.Experience operating systems in production, including observability, debugging, reliability, incident response, and performance/cost optimization.Hands-on experience with LLM inference and/ ...

Description Senior AI/ML Computational Scientist Career Level: Senior Manager/Associate Director YOU ARE As a senior AI/ML Computational Scientist, you will design, build, and operationalize artificial intelligence and machine learning solutions for enterprise clients, combining custom models with cloud and third-party … include big data, high-performance compute, engineering simulations, scientific compute, grid and cloud computing, distributed networks Established experience in building and deploying AI/ML based software to a cloud environment. PREFERRED QUALIFICATION Proficiencyin Python andpython-based AI/ML framework and familiarity with relevant libraries and frameworks (e.g., TensorFlow ...

four consecutive years as one of the World’s Best Management Consulting Firms.Our Solutions & AI Labs (SAIL) practice are looking for experienced AI/ML Engineers to join the team!The AI/ML Engineer role will lead the delivery of AI-enabled solutions embedded in our clients' teams, combining … Learning solutions directly embedded into business processes. We support clients across a number of industries and offer deep expertise in AI/ML, Cloud, Platform Engineering, and Managed Solutions. What you will be doing As a Senior Consultant in SAIL, you will own and lead consultancy engagements ...