1 to 25 of 4,145 Machine Learning Jobs in the UK

languages such as Python, Java, or C++, writing clean, efficient, and maintainable code for production grade AI solutions. Hands-on experience deploying AI/ML models to production environments, with a good understanding of MLOps practices including CI/CD pipelines, model versioning, and monitoring. Experience with cloud platforms … Azure, or GCP) and cloud-native AI tools such as SageMaker, Vertex AI, or Azure ML Studio. Working knowledge of containerization technologies (e.g., Docker) and orchestration tools (e.g., Kubernetes) to build and manage scalable AI solutions. Skills in data engineering, including building data pipelines, data wrangling, and integrating AI solutions ...

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 ...

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 ...

professional judgement. What You'll DoLead the end-to-end delivery of data science solutions including PoCs, MVPs and production deployments. Develop and prototype ML models to solve complex business challenges using modern techniques and tooling. Collaborate closely with engineers, domain experts, and business teams to translate requirements into deliverables … improve efficiency and accelerate insight. Guide and coach data science pods, supporting skill development and solution design. Act as a subject matter expert on ML architecture, model calibration, and productionisation, promoting responsible AI practices and scalable model governance where applicable. What We're Looking ForHands-on experience building and deploying ...

technical direction for the team's deliverables. Design, develop and implement highly scalable and efficient data pipelines using advanced Python (Pandas, web scraping and machine learning libraries), SQL (including advanced optimisation techniques) and Apache Airflow. Lead the extraction, transformation and loading (ETL) of large and complex datasets, including … within a trading or financial services environment. In-depth expertise in Python (Pandas, web scraping libraries such as Selenium, Beautiful Soup and Requests, and machine learning libraries such as TensorFlow and PyTorch). Generative AI techniques including agents, skills, prompt engineering, RAG, AI SDLC, context engineering and evaluations. ...

technical direction for the team's deliverables. Design, develop and implement highly scalable and efficient data pipelines using advanced Python (Pandas, web scraping and machine learning libraries), SQL (including advanced optimisation techniques) and Apache Airflow. Lead the extraction, transformation and loading (ETL) of large and complex datasets, including … within a trading or financial services environment. In-depth expertise in Python (Pandas, web scraping libraries such as Selenium, Beautiful Soup and Requests, and machine learning libraries such as TensorFlow and PyTorch). Generative AI techniques including agents, skills, prompt engineering, RAG, AI SDLC, context engineering and evaluations. ...

Test, Smart Audit and Smart Shield), Employee Document Management and Pay Transparency Analyzer. You will lead the design and delivery of advanced AI/ML solutions that improve the functionality, scalability, and efficiency of our Workday product suite. You will focus on cutting edge innovations, such as predictive analytics … problems. Strong programming skills in Python, with an emphasis on writing clean, efficient, and maintainable code to enable scalable and production-grade AI/ML solutions. Extensive experience with machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch), with the ability to design, implement, and optimise scalable solutions while ...

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 ...

speed, reliability, and operational excellence. Key ResponsibilitiesRapid Prototyping & Application Development: Lead the end-to-end development of applications that integrate and leverage AI/ML models, from architectural design, data schema design, data pipeline construction, and rapid prototyping to initial deployment and operationalization, utilizing cloud-native services (e.g., serverless, containerization … managed AI/ML platforms) and CI/CD pipelines for accelerated delivery. Implement robust MLOps practices to streamline model deployment, monitoring, and lifecycle management in cloud environments, including data versioning, feature store integration, and data pipeline management. Business Partnership & Solution Architecture: Collaborate closely with business and engineering teams ...

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 ...

their career to new heights. Join the ranks of top talent at one of the world's most influential companies. As an Applied AI ML Lead - Vice President at JPMorgan Chase within the International Private Bank (IPB) Technology Artificial Intelligence and Machine Learning (AIML) Team, you provide deep … responsible to the Head of AIML in IPB Tech for the end-to-end design, build, and production delivery of priority IPB AI/ML use cases, with particular focus on agentic AI applications, generative AI guardrails, and production ML supporting advisor and client journeys. Job responsibilities Owns ...

their career to new heights. Join the ranks of top talent at one of the world's most influential companies. As an Applied AI ML Lead - Vice President at JPMorgan Chase within the International Private Bank (IPB) Technology Artificial Intelligence and Machine Learning (AIML) Team, you provide deep … responsible to the Head of AIML in IPB Tech for the end-to-end design, build, and production delivery of priority IPB AI/ML use cases, with particular focus on agentic AI applications, generative AI guardrails, and production ML supporting advisor and client journeys. Job responsibilities Owns ...

Applied AI/ML Lead Engineer in our Applied AI ML - Python & Agentic AI team, you will design, build, and productionize Generative AI and Agentic AI solutions. The ideal candidate brings a balanced mix of modern AI/ML delivery (LLMs/SLMs, RAG, tool-using agents, evaluation, MLOps … engineering assets (templates, routing, guardrails), and implement automated evaluation to improve quality over time. Build and maintain data pipelines and processing workflows required for ML/GenAI use cases using cloud services. Apply MLOps practices across the lifecycle: experimentation, versioning, CI/CD, deployment, monitoring, and maintenance for models/ ...

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 ...

responsible to the Head of AI, IPB Tech for the end-to-end design, build, and production delivery of priority IPB AI/ML use cases, with particular focus on agentic AI applications, generative AI guardrails, and production ML supporting advisor and client journeys. Job responsibilities Owns … delivery of priority IPB AI/ML use cases, from problem framing and business case through to deployed, monitored production services with measurable advisor and client impact Leads the engineering build of agentic AI and LLM-powered products serving IPB advisors and clients across international markets Sets the engineering quality ...

part of something bigger. As a Senior Data Scientist within Kainos' Workday Products division, you'll be responsible for developing high quality AI and ML solutions for our fast growing suite of Workday products – including Kainos Smart (Smart Test, Smart Audit and Smart Shield), Employee Document Management and Pay Transparency … Analyzer. You will work on the design and delivery of advanced AI/ML solutions that improve the functionality, scalability and efficiency of our Workday product suite. You may also carry some formal line management responsibilities, including appraisals, for more junior members of the team. Essential Experience: Typically ...

outcomes. As an FDE, you will act as a trusted technical advisor, solution architect, and hands-on engineer, helping customers successfully adopt Generative AI, Machine Learning, Agentic AI, LLM-based applications, and AI-driven automation solutions. What You'll Do Customer Engagement & Solution Delivery: Partner with customers … evaluation frameworks, guardrails, and monitoring platforms. Experience with Agentic AI and Multi-Agent Systems. Relevant certifications in Azure AI, Azure OpenAI, AWS AI/ML, GCP AI, or related technologies. Expertise You'll Bring Your expertise in AI technologies, strong technical skills, and customer engagement experience will be crucial ...

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 ...

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 ...

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 autonomously in a small, senior team, partnering closely with Founders. Strong analytical judgement, communication skills, and attention to detail. Experience with designing and refining large ...

development — prompt engineering, fine-tuning, RAG pipelines, context window management Agentic AI frameworks — LangChain, LangGraph, AutoGen, or similar; building multi-step autonomous workflows Machine Learning — model development, training, evaluation … deployment APIs & backend development — FastAPI, REST APIs, microservices architecture Vector databases & embeddings Cloud platforms — Azure GCP, or AWS; deploying and managing AI/ML workloads at scale Version control & MLOps — Git, CI/CD pipelines, model versioning, monitoring in production Data handling Required — Experience & Mindset Demonstrated end-to-end delivery ...

development — prompt engineering, fine-tuning, RAG pipelines, context window management Agentic AI frameworks — LangChain, LangGraph, AutoGen, or similar; building multi-step autonomous workflows Machine Learning — model development, training, evaluation … deployment APIs & backend development — FastAPI, REST APIs, microservices architecture Vector databases & embeddings Cloud platforms — Azure GCP, or AWS; deploying and managing AI/ML workloads at scale Version control & MLOps — Git, CI/CD pipelines, model versioning, monitoring in production Data handling Required — Experience & Mindset Demonstrated end-to-end delivery ...

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 ...