1 to 25 of 3,232 Machine Learning Jobs in the UK

Python, Java, or C++. Emphasis on writing clean, efficient, and maintainable code for production-grade AI solutions. Proven experience in deploying AI/ML models to production environments, ensuring scalability, reliability, and performance. Familiarity with MLOps practices, including CI/CD pipelines, model versioning, and monitoring. Comprehensive experience with cloud … platforms (AWS, Azure, or GCP) and cloud native AI tools, such as SageMaker, Vertex AI, or Azure ML Studio. Ability to design and deploy cloud-based AI solutions. Proficiency in using containerization technologies (e.g., Docker) and orchestration tools (e.g., Kubernetes) to build and manage scalable AI solutions. Strong skills ...

Posted Todayjob requisition id: R0121775# Data Science Manager## Are you an experienced Data Science leader with a passion for building and scaling AI/ML products Lead a team of exceptional Data Scientists and ML Engineers building next-generation AI solutions for financial markets. Drive innovation using **LLMs, Generative … Engineering teams to **productionize AI solutions and drive operational excellence**.* Build, mentor, and lead high-performing teams of **Data Scientists and AI/ML practitioners**.* Set clear goals, drive accountability, and support career growth and development.* Lead performance management, coaching, feedback, and talent development activities.* Foster a culture ...

research. Strong software engineering skills, with a track record of building and maintaining production‐quality systems. Expert‐level Python experience with numerical, statistical, or ML libraries (e.g. NumPy, pandas, PyTorch, JAX, TensorFlow). Deep understanding of statistical modelling, optimisation, or machine‐learning techniques. Experience building and operating backend … systems and data pipelines in a cloud environment (e.g. AWS, GCP, or Azure). Experience validating, testing, and deploying quantitative or ML models. Comfortable working with high ownership in a small, senior team, partnering closely with Founders. Strong analytical judgement, communication skills, and attention to detail. Desired Experience with designing ...

platforms. Contribute to model lifecycle management tooling: model inventory, workflow orchestration, approvals, periodic reviews, and audit‐ready evidence generation. AI Enablement Implement AI/ML components within the model workflow, including LLM‐based automation for model documentation generation and updating, intelligent data quality checks, and workflow assistance. Integrate AI tooling … into a controlled, auditable, production‐grade environment, with appropriate testing, monitoring, and governance controls. Stay current with developments in applied AI/ML and evaluate their applicability to risk technology use cases. Collaboration & Standards Work within a cross‐functional agile team alongside quants, validators, data engineers, and program management. Promote ...

Knowledge and Experience Essential: 8-10 years of experience in software architecture or technical lead roles with 4-5 years focused on AI/ML platforms and data-intensive systems Proven experience designing end-to-end architectures or processes for AI/ML systems in production environments supporting large user … management systems Demonstrated ability to work effectively with both technical teams and business stakeholders, translating between technical and business language Proficiency in AI/ML technologies including model training platforms, deployment frameworks, data pipelines, and monitoring tools Experience with distributed systems design, API architecture, and microservices patterns for building scalable ...

cases through modern data products and data platforms. Design and implement reusable data products, semantic models and analytics capabilities that support reporting, machine learning and GenAI workloads. Drive adoption of AI Engineering, MLOps and LLMOps best practices across development, deployment, monitoring and governance. Champion security, resilience, privacy, Responsible … improve efficiency, reliability and developer productivity through automation and platform engineering. Mentor, coach and develop engineering teams, fostering a culture of innovation, continuous learning and engineering excellence. Why join us? From building a truly sustainable business to creating a place where people love to work, we’re looking ...

high performing team of applied AI experts to drive innovation and new capabilities in the Commercial & Investment Bank. As an Applied AI/ML Senior Associate Machine Learning Engineer in the Applied AI ML team at JPMorgan Commercial & Investment Bank, you will be at the forefront of combining … qualifications, capabilities, and skills Masters or PhD in a quantitative discipline, e.g. Computer Science, Mathematics, Statistics Solid understanding of fundamentals of statistics, optimization and ML theory. Familiarity with popular deep learning architectures (transformers, CNN, autoencoders etc.) Specialism or well‐researched interest in NLP Broad knowledge of MLOps tooling ...

software solutions for XVA risk systems, writing and reviewing production-quality code while ensuring alignment with enterprise architecture standards.* Build and integrate AI and Machine Learning solutions into core XVA workflows — applying Generative AI tooling to automate processes, improve analytical accuracy, and measurably accelerate engineering output.* Take … infrastructure as code.* Master's degree in Computer Science, Finance, or a related field; professional certifications such as PMP, CSM, or AI/ML credentials are a plus.* Prior experience applying AI or automation specifically within risk analytics, trading systems, or regulatory reporting workflows.This job description provides a high-level ...

write code, build prototypes, and lead by example. Team Building & Mentorship: Recruit, hire, and mentor a high‐performing, agile team of software and machine‐learning engineers. Foster a culture of innovation, excellence, and accountability. Strategic Roadmapping: Partner closely with product management and senior business leaders in banking … Collaboration: Partner effectively with horizontal AI platform teams, enterprise architecture, and external vendor partners to leverage existing capabilities, influence roadmaps, and accelerate delivery. AI & ML Integration: Drive the strategy for integrating and operationalizing Large Language Models (LLMs), agentic frameworks (e.g., Google ADK, LangChain), and other AI/ML technologies ...

write code, build prototypes, and lead by example. Team Building & Mentorship: Recruit, hire, and mentor a high-performing, agile team of software and machine learning engineers. Foster a culture of innovation, excellence, and accountability. Strategic Roadmapping: Partner closely with product management and senior business leaders in banking … Collaboration: Partner effectively with horizontal AI platform teams, enterprise architecture, and external vendor partners to leverage existing capabilities, influence roadmaps, and accelerate delivery. AI & ML Integration: Drive the strategy for integrating and operationalizing Large Language Models (LLMs), agentic frameworks (e.g., Google ADK, LangChain,), and other AI/ML technologies ...

Design, train, and deploy production-grade ML models. About the Role As a Senior Machine Learning Engineer, you will lead the design, development, and deployment of production-grade machine learning systems for global enterprise clients. You'll work at the intersection of research and engineering, translating … cutting‐edge papers into scalable, reliable solutions. This is a high‐impact role where you'll mentor junior engineers, shape our ML architecture, and collaborate directly with clients to solve their most complex challenges. Design and implement end-to-end ML pipelines from experimentation to production Lead model development across ...

equip students with an understanding of database systems, internet technologies, data, cyber security, networking, and business information systems. You will undertake all aspects of learning, teaching and assessment of students and keep up to date with latest developments in your field and student support practices. Responsibilities include: All aspects … planning, delivering, and assessing student work, ensuring that all learning outcomes are met Developing, updating, and improving course materials as appropriate Using a variety of learning and teaching methods/materials Actively engaging in staff development activities, peer observations, meetings and other administrative duties Understanding and keeping ...

equip students with an understanding of database systems, internet technologies, data, cyber security, networking, and business information systems. You will undertake all aspects of learning, teaching and assessment of students and keep up to date with latest developments in your field and student support practices. Responsibilities include: All aspects … planning, delivering, and assessing student work, ensuring that all learning outcomes are met Developing, updating, and improving course materials as appropriate Using a variety of learning and teaching methods/materials Actively engaging in staff development activities, peer observations, meetings and other administrative duties Understanding and keeping ...

equip students with an understanding of database systems, internet technologies, data, cyber security, networking, and business information systems. You will undertake all aspects of learning, teaching and assessment of students and keep up to date with latest developments in your field and student support practices. Responsibilities include: All aspects … planning, delivering, and assessing student work, ensuring that all learning outcomes are met Developing, updating, and improving course materials as appropriate Using a variety of learning and teaching methods/materials Actively engaging in staff development activities, peer observations, meetings and other administrative duties Understanding and keeping ...

comprehensive monitoring systems to track system performance, detect anomalies, and promptly troubleshoot issues, ensuring the stability and efficiency of AI operations. Implement ML Ops and Cloud Best Practices: Apply ML Ops principles to streamline model lifecycle management, including versioning, testing, and deployment. Use cloud-native tools and frameworks to improve … languages. Hands-on experience working with cloud services and deployment tools. Solid understanding of microservice architecture, containerization (Docker, Kubernetes), and automation frameworks. Knowledge of ML Ops, LLMOps, and AI system integration processes. Desired Skills and Abilities: Practical experience with Generative AI and large language models (LLMs). Prior involvement with ...

translate the results of our Research into re‐usable libraries, tooling and products. Foster a nurturing environment for colleagues with less experience in ML/Engineering for them to grow and you to mentor. What you bring to the table Enthusiasm about developing machine learning solutions, especially deep … large/foundation models. Ideally >2 years of experience in a data-driven role in a professional setting , with exposure to: scaling and optimising ML models, training and serving foundation models at scale (federated learning a bonus); distributed computing frameworks (e.g., Spark, Dask) and high-performance computing frameworks ...

industry leaders and advance your career in a dynamic, inclusive environment. Join us to drive innovation and make a difference. As an Applied AI & ML Lead in the Market Operations team, you will drive the design and delivery of AI/ML solutions that enhance and transform Market Operations. … successful implementation and scaling of AI-driven tools. You will identify opportunities, set technical direction, and deliver measurable impact through innovative AI/ML applications. Your leadership will help foster a culture of collaboration and continuous learning. Job Responsibilities: Lead the development, implementation, and end-to-end delivery of advanced ...

industry leaders and advance your career in a dynamic, inclusive environment. Join us to drive innovation and make a difference. As an Applied AI & ML Lead in the Market Operations team, you will drive the design and delivery of AI/ML solutions that enhance and transform Market Operations. … successful implementation and scaling of AI-driven tools. You will identify opportunities, set technical direction, and deliver measurable impact through innovative AI/ML applications. Your leadership will help foster a culture of collaboration and continuous learning. Job Responsibilities: Lead the development, implementation, and end-to-end delivery of advanced ...

high performing team of applied AI experts to drive innovation and new capabilities in the Commercial & Investment Bank. As an Applied AI/ML Senior Associate Machine Learning Engineer in the Applied AI ML team at JPMorgan Commercial & Investment Bank, you will be at the forefront of combining … qualifications, capabilities, and skills Masters or PhD in a quantitative discipline, e.g. Computer Science, Mathematics, Statistics Solid understanding of fundamentals of statistics, optimization and ML theory. Familiarity with popular deep learning architectures (transformers, CNN, autoencoders etc.) Specialism or well-researched interest in NLP Broad knowledge of MLOps tooling ...

deployment and ongoing model performance, with strong object-oriented programming, machine learning and statistical skills, and experience taking models into production, designing ML pipelines and working with MLOps, CI/CD and Azure. Key Responsibilities Delivery of data science products Leading data science projects end-to-end, from … practice, covering pipeline orchestration, model versioning, automated deployment, monitoring and retraining. Cloud based machine learning delivery, ideally on Azure (Azure ML, Azure DevOps), with equivalent AWS or GCP experience considered. SQL and relational data modelling, with the ability to work efficiently against large datasets. Statistical foundations sufficient ...

seeking an experienced, technical, and hands‐on Autonomy Data Manager to grow and lead a talented team composed of Data Scientists, Data Engineers and ML Ops Engineers, working in the Autonomy team to deliver data driven Planning and Perception solutions. You will lead the team to drive the creation … provide technical guidance in the design, development, deployment, optimization, and evaluation of state‐of‐the‐art data algorithms, data efficiency and pipelines to enable ML model performance with a focus on iteration speed, scalability and overall cost efficiency. Drive a culture of rigorous statistical evaluation to measure, validate and implement ...

ofAI and Machine Learning solutions directly embedded into business processes. We support clients acrossa number ofindustries and offer deepexpertisein AI/ML, Cloud, Platform Engineering, and Managed Solutions. What you will be doing As a Senior Manager in SAIL, you will own and lead consultancy engagements … winning the work, through to delivery governance and team leadership. You will bring SME-level depth in at least one of AI/ML Engineering, Platform Engineering, or Software Engineering, and apply it to create real, lasting value for our clients. Although we do not expect ...

others to deliver advanced AI and data solutions at citizen scale. Our 150-strong AI and Data Practice brings together deep expertise in machine learning, generative AI, agentic AI and data. We are pioneers in responsible AI, having authored the UK government's AI Cyber Security Code … 2.1 degree in Computer Science, AI, Data Science, Statistics or in a similar quantitative field. Demonstrable experience of deploying modern AI/ML solutions into production, including prompt engineering, retrieval-augmented generation (RAG), model evaluation, and monitoring using metrics (e.g. precision, recall, NDCG and drift detection). Strong Python skills ...

practices (SLOs, error budgets, runbooks) and leads production incident response and post-incident review Builds and operates observability across the team's AI/ML services (metrics, logging, tracing, alerting) Automates infrastructure provisioning and configuration through infrastructure-as-code Implements operational security, secrets management, and access controls to firm-wide … environment Master's degree in Computer Science, Engineering, or a related technical field (or equivalent applied experience) Preferred qualifications, capabilities, and skills Experience operating ML/LLM workloads in production (MLOps, inference reliability, cost/performance management) Experience within financial services technology Familiarity with JPM-internal platform, cloud, and observability ...

rapid experimentation while meeting production standards for latency, scale, monitoring, SLOs, playbooks, and operational excellence. Partner closely with - and raise the technical bar for - ML engineers, product engineers, data scientists, and platform teams across DoorDash, Wolt, and Deliveroo to turn emerging GenAI capabilities into durable platform primitives. Set technical direction … software engineering Deep backend engineering fundamentals, especially in Python and distributed systems. Track record of designing and owning 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. Deep hands-on experience with ...