1 to 25 of 1,495 Machine Learning Jobs in the UK

listen in their homes (and beyond), the Product Data team uses data to guide and influence the product direction and improve the customer experience. Sonos is looking for a Machine Learning Engineer to join the Product Data team and contribute to building innovative, data-driven solutions that enhance customer experiences and product intelligence. You will work alongside engineers … and analysts to develop machine learning models that power experimentation, personalization, and proactive customer insights. This is an excellent opportunity for someone early in their machine learning career to gain hands-on experience developing and deploying real-world solutions for a global consumer technology brand. What You'll Do Collaborate with other machine learning engineers on the development and deployment of machine learning models across product and customer intelligence initiatives. Work with Data Analysts to understand data patterns, user behaviors, and analytical insights that inform model development. Partner with Data Engineers to gain hands-on experience in designing and maintaining scalable machine learning pipelines and data workflows. Collaborate cross More ❯

Description The Chief Data & Analytics Office (CDAO) at JPMorgan Chase is responsible for accelerating the firm's data and analytics journey. As a part of CDAO, The Machine Learning Center of Excellence (MLCOE) partners across the firm to shape, create, and deploy Machine Learning Solutions for our most challenging business problems. This includes ensuring the quality … to generate insights and drive decision-making. The CDAO is also responsible for developing and implementing solutions that support the firm's commercial goals by harnessing artificial intelligence and machine learning technologies to develop new products, improve productivity, and enhance risk management effectively and responsibly. As a Summer Associate within the MLCOE, you will apply sophisticated machine … and more. Your project will have direct impact on JPMorgan's businesses, will be integrated into our product pipelines, or be part of published research in top AI/ML conferences. Full-time employment offers may be extended upon successful completion of the program within our hybrid work model. Job responsibilities Research and explore new machine learning methods More ❯

Machine Learning Operations Engineer Our financial services client based in London is looking to recruit a Machine Learning Operations Engineer ASAP. The position will be a Hybrid role be working from home and their offices in London. To be considered for the role you must have the following essential skills & experience: Key Skills & Experience Model development … Work collaboratively with actuarial analysts to develop machine learning and statistical models to predict outcomes, related to pension schemes, such as life expectancy, default risk, or investment returns. Identify appropriate machine learning algorithms and apply them to enhance predictions, automate decision-making processes, and improve client offerings. Machine Learning Operations: Responsible for designing, deploying … team and non-technical stakeholders within the company. Technical Skills required Previous experience in designing, building, optimising, deploying and managing business-critical machine learning models using Azure ML in Production environments. Experience in data wrangling using Python, SQL and ADF. Experience in CI/CD and DevOps/MLOps and version control. Familiarity with data visualization and reporting More ❯

This is a leadership role where you’ll not only design and build advanced machine learning solutions but also line-manage engineers, coordinate delivery across high-impact ML projects, and define the technical bar across the team. Your compensation reflects both the strategic leadership scope and technical excellence expected in this role. What you'll be doing: Lead … and guiding career development. Set the technical direction for GenAI and retrieval-based systems, ensuring consistent architecture, tooling, and research-to-production workflows. Act as delivery owner across multiple ML streams, coordinating timelines, resources, and cross-functional collaboration. Drive best practices for scalable, reproducible, and robust ML system development. Be hands-on when needed, contributing to model development and high … trends, bringing innovative approaches to real-world problems. Promote a culture of experimentation, open communication, and continuous learning across the team. What you'll bring: Experience line-managing ML engineers and leading delivery across multiple, concurrent ML workstreams. Strong technical background in machine learning engineering — with production-level experience in Python, SQL, and frameworks like PyTorch or More ❯

through our Hybrid Work Model. Job Description Key Responsibilities May Include: Collaborate with key stakeholders to identify business challenges, translating ambiguous problems into structured analyses using statistical modelling and machine learning algorithms. Lead the selection, validation, and optimization of models to discover meaningful patterns and insights, ensuring models remain relevant, reliable, and scalable. Drive continuous integration and deployment … of data science solutions, optimizing performance through advanced machine learning techniques, code reviews, and best practices. 'Develop and deliver sophisticated visualizations, dashboards, and reports translate complex data into clear, actionable insights for business stakeholders. Present technical solutions to business stakeholders, using creative methods to explain complex concepts, increase understanding, and encourage solution adoption. Mentor and develop junior data … and experience following CRISP-DM data science lifecycle. Expertise taking projects from ideation or experimental Jupyter notebooks to full production deployment. Strong programming skills in Python, with familiarity in ML libraries/frameworks such as TensorFlow, PyTorch, and Scikit-learn. Experience with MLOps practices including model drift detection, decay, A/B testing, integration testing, differential testing, Python package building More ❯

the beginning of our journey - and we are very excited about our plans for growth over the coming year and beyond The role We are now looking for a Machine Learning Engineer to build and deliver innovative AI products to our customers. Your software expertise and machine learning knowledge will help transform our customers' manual processes … analytical skills to understand customer challenges and collaborate with them to leverage our AI in the automation of their work. Initially, you will provide hands-on support for our machine learning models as they come to market but then will gradually develop self-service tools that empower customers to achieve value independently. As part of this role, you … development of our Virtual Agent development platform that scales with our product strategy. Ensure our AI services maintain high standards of reliability, observability, availability, and performance. Participate in our machine learning community to influence how we implement machine learning and computer vision technologies, shaping Unitary's future. Take ownership of customer outcomes with the autonomy to More ❯

This is a hands-on leadership role: you’ll set the AI strategy, design and scale production NLP and machine learning systems, and grow a high-performing ML team - while closely partnering with Product and Engineering to deliver real, measurable impact for customers. This VP of AI & Machine Learning will Take ownership of the company’s … AI roadmap — from concept to production. Build and scale NLP and ML models that turn complex organisational data into meaningful insights. Lead and develop a small ML engineering team, acting as a player-coach. Establish MLOps, monitoring, governance, and responsible AI practices. Work cross-functionally with Product, Engineering, and Customer teams. Represent AI and technology thinking to customers, partners, and … knowledge of MLOps (model versioning, monitoring, evaluation, drift detection). Hands-on expertise in Python, PyTorch/TensorFlow, HuggingFace, and vector search technologies. Experience leading or mentoring small, senior ML/data teams. Ability to translate technical work into clear product and business value. A pragmatic, delivery-focused mindset — comfortable in fast-moving, evolving environments. The tech environment: Python, PyTorch More ❯

This is a hands-on leadership role: you’ll set the AI strategy, design and scale production NLP and machine learning systems, and grow a high-performing ML team - while closely partnering with Product and Engineering to deliver real, measurable impact for customers. This Head of AI & Machine Learning will Take ownership of the company’s … AI roadmap — from concept to production. Build and scale NLP and ML models that turn complex organisational data into meaningful insights. Lead and develop a small ML engineering team, acting as a player-coach. Establish MLOps, monitoring, governance, and responsible AI practices. Work cross-functionally with Product, Engineering, and Customer teams. Represent AI and technology thinking to customers, partners, and … knowledge of MLOps (model versioning, monitoring, evaluation, drift detection). Hands-on expertise in Python, PyTorch/TensorFlow, HuggingFace, and vector search technologies. Experience leading or mentoring small, senior ML/data teams. Ability to translate technical work into clear product and business value. A pragmatic, delivery-focused mindset — comfortable in fast-moving, evolving environments. The tech environment: Python, PyTorch More ❯

the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Lead Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data … Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Lead the design and analysis of A/B tests and offline experiments to evaluate model efficacy … bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Advanced proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high More ❯

hours and opportunities to contribute to frontier AI evaluation and research. Key Responsibilities Evaluate and compare AI-generated research plans for clarity, feasibility, and technical soundness. Design and compile ML tasks based on real-world challenges and research competitions. Draft detailed, executable natural language plans for machine learning workflows. Implement and validate research plans in Python within a … concise, objective feedback. Ideal Qualifications 5+ years of experience in applied machine learning or a PhD in machine learning or related fields. Strong understanding of ML research methodologies, experimental design, and evaluation practices. Excellent analytical and technical writing skills. Experience with reproducibility or benchmarking in ML research preferred. Detail-oriented and able to deliver high-quality …/hour Payment: Weekly via Stripe Connect Contract Type: Independent contractor engagement Structure: Remote, milestone-based evaluation with flexible scheduling Application Process Submit your resume or CV highlighting relevant ML research or engineering experience. Complete a short AI-based interview and a brief questionnaire about your experience with reproducibility and model benchmarking. Selected candidates will receive detailed onboarding materials and More ❯

Engineer, you'll sit at the intersection of data science, engineering, and commercial strategy, working closely with our product and core engineering teams to translate business challenges into deployable ML solutions. You'll have the autonomy to experiment, iterate, and bring ideas to production that directly impact revenue and user engagement. This role would suit a Machine Learning Engineer with at least three years commercial ML/AI experience gained working In a mission focussed, product led business. In return this ML Engineer will receive extensive growth and personal development opportunities as the business transitions away from legacy engineering practices. This ML Engineer based near Birmingham should have most of the following key skills: - Demonstrated experience delivering … business impact and growth through ML solution design and development - Proven experience in Python, TensorFlow/PyTorch, and modern ML frameworks. - Strong background in data modelling, feature engineering, and model deployment. - Experience with SQL, cloud platforms (AWS/GCP/Azure), and API integration. - A commercial mindset - you think in terms of ROI, not just model accuracy. - Excellent communication skills More ❯

this role, you won't just analyse data; you'll answer the critical questions that drive our strategy. We're looking for someone to use advanced data science and machine learning to uncover the 'why' behind customer behaviour, such as identifying complex churn triggers for our energy customers. You will also develop and own the models that quantify … Lifetime Value (LTV) and Customer Acquisition Cost (CAC). This isn't a research role. We need a "full-stack" data scientist who can own the end-to-end ML lifecycle. You will take your ideas from initial Proof of Concept (POC) and exploratory analysis all the way through to building, deploying, and maintaining production-ready models, collaborating closely with … our Machine Learning Engineers. We work together. Your team and the people you will work with... Our Data teams are small, empowered, and cross-functional, taking full ownership of the solutions they build. We adopt the technologies that best support our goals and continuously raise the bar on how we deliver value. UW’s Data team is a More ❯

Machine Learning Engineer Machine Learning Engineer - AI for Advanced Materials - Oxford/Remote (UK) (Tech stack: Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, AWS, Azure, GCP, Pandas, NumPy, SciPy, CI/CD, MLOps, Data Visualization, Bayesian Modelling, Probabilistic Programming, Terraform) We're looking for a Machine Learning Engineer to join a rapidly … printing , our client is transforming the way metal components are conceived, tested, and produced - enabling breakthroughs in aerospace, energy, and beyond. This is a rare chance to apply your ML expertise to problems that have a tangible, physical impact - from inventing new alloys to optimising complex manufacturing processes. You'll collaborate with leading data scientists, engineers, and materials researchers to … build models that drive real-world innovation. Expect to design, validate, and deploy state-of-the-art ML pipelines that move seamlessly from concept to production. If you thrive in fast-paced, intellectually charged environments where every model could change an industry, you'll fit right in. Our client is seeking Machine Learning Engineers with experience in some More ❯

Role/Job title Data Scientist - Azure ML Ops & Databricks Work Location Wokingham, UK Role type - Permanent/Fixed Term/Contracting Contracting Mode of working Hybrid/office based Office based 5 Days in Office If Hybrid, how many days are required in office? NA Number of positions 1 Duration of assignment 06 Months Any other working conditions - travel …/on call/shifts To be published on job boards from below onwards The Role: Data Scientist - Azure ML Ops & Databricks Your responsibilities: Data Analysis & Modeling: Utilize Python for advanced data analysis, exploration, and processing to uncover actionable insights. Develop and implement machine learning models and algorithms using Python , Azure Machine Learning , and Databricks . … ML Ops & Deployment: Manage and optimize ML Ops processes within the Azure environment, ensuring efficient deployment, monitoring, and maintenance of models. Collaboration & Business Alignment: Work closely with cross-functional teams to understand business requirements and translate them into data-driven solutions. Data Engineering & Governance: Develop and maintain large-scale data models to support analytics and reporting needs. Ensure data quality More ❯

Machine Learning Engineer (Python/MLE ) 6 Month Contract £650 - £750 Remote Umbrella Urgent Start We are looking for a number of MLE/Machine Learning Engineers for a critical 6 month contract with a household name. This role is essential for maintaining the stability and performance of their core data and Machine Learning … November. This is a deeply technical engineering role focused less on new feature development and more on reliability and fixes. Key Skills: Investigating and debugging complex data flow and Machine Learning issues within a live, high impact production environment. Extensive Python, NumPy and Pandas is required for this role. You must demonstrate a deep commercial background in the … Cloud Experience: Solid experience with any major public cloud provider (GCP, AWS, or Azure). Experience with BigQuery would be good. Machine Learning: Experience supporting and understanding ML pipelines and models in a production setting. Direct experience with Google Cloud Platform, BigQuery, and associated tooling. Experience with workflow tools like Airflow or Kubeflow. Familiarity with dbt (Data Build More ❯

at the heart of an established data function, working on real production workloads rather than prototypes. You'll play a key role in shaping how intelligent automation, LLMs and ML-driven services are designed, deployed and continuously improved. What you'll be working on * Designing and delivering Gen AI and LLM-driven applications* Building and maintaining machine learning pipelines and data workflows* Developing cloud-native (serverless) ML components within a distributed engineering team* Improving existing ML systems and identifying opportunities for optimisation* Supporting sprint planning, estimation and shaping a healthy product backlog What you'll need to bring * Strong hands-on Python skills and solid grounding in algorithms and software engineering* Experience designing ML/AI solutions … and working with common architecture patterns* Background in serverless data/ML pipelines (Azure preferred, AWS/GCP welcome)* Proficiency in SQL and NoSQL data stores* Broad understanding of machine learning methods (regression, tree-based models, clustering, deep learning, attention models, transformers, vector representations)* Ability to explain technical concepts clearly to a range of stakeholders* Confidence estimating More ❯

Instructor to support delivery across the Machine Learning Engineer (Level 6) Apprenticeship and wider commercial programmes. If you're a passionate technologist who loves bringing complex ML concepts to life — from maths foundations to real-world deployment — this is your chance to make a real impact. What you'll do You'll play a key role in … helping learners and professionals build deep, practical ML capability. Day-to-day, you'll: ? Deliver engaging teaching sessions covering the full ML lifecycle — data prep, model training, evaluation, deployment and monitoring at scale. ? Explain the maths behind ML models (linear algebra, calculus, probability, stats) in an accessible, engaging way. ? Support learners throughout their apprenticeship journey alongside Learner Success Coaches. ? Contribute … delivery meets the standards expected by Ofsted, ESFA and other awarding bodies. What we're looking for You'll need to bring: Strong industry experience in end-to-end ML projects — from data wrangling and model building to deployment and monitoring. Confident teaching ability — whether you've formally taught, mentored or coached technical teams. Mathematical depth — clear understanding of the More ❯

This temporary role requires an ML Quant Engineer with expertise within an Investment Bank. The position is based in London and involves developing and implementing machine learning models to support financial decision-making. Client Details The hiring organisation is a large entity within the financial services industry. Description Design and implement machine learning models for financial … applications, with a focus on derivatives pricing, risk analytics, and market forecasting. Build scalable ML pipelines to process large volumes of financial data efficiently. Develop deep learning architectures for time series prediction, anomaly detection, and pattern recognition in market data. Optimise model performance using techniques such as hyper-parameter tuning, ensemble methods, and neural architecture search. Collaborate with quantitative … analysts to align ML models with pricing methodologies and identify opportunities for innovation. Support the deployment of ML solutions into production systems for real-time risk management and pricing automation. Profile Advanced Machine Learning Expertise - Demonstrates deep understanding of ML algorithms (supervised, unsupervised, reinforcement learning) and has hands-on experience with deep learning architectures like RNNs More ❯

Snapshot Science is at the heart of everything we do at Google DeepMind. We are committed to using AI and machine learning to accelerate scientific discovery and tackle some of humanity's biggest challenges. The development of fault-tolerant quantum computing represents one of the most profound scientific and computational challenges of our era. In the Science team … progress in this field. This is an opportunity to conduct groundbreaking research at the intersection of quantum computing and artificial intelligence. Our team is focused on leveraging cutting-edge machine learning to push the boundaries of what's possible in quantum simulation and algorithm development. You will join a multidisciplinary team of world-class researchers and engineers to … ideas, run experiments, and publish your findings, with the goal of advancing quantum science through the application of artificial intelligence. Key responsibilities: Design and execute research projects, applying modern ML techniques (including generative AI) at the intersection of quantum computing and machine learning. Identify, develop and test classical and quantum algorithms with a focus on real-world quantum hardware. More ❯

the beginning of our journey - and we are very excited about our plans for growth over the coming year and beyond The role We are now looking for a Machine Learning Research Engineer to help build and deliver a platform that can automatically create Virtual Agents for operational processes currently undertaken manually using browser-based UIs. An important … our customer-facing technical teams Utilise best-in-class capabilities to deliver these capabilities Research, invent and create novel capabilities where gaps in industry require it Participate in our machine learning community to influence how we implement machine learning and computer vision technologies, shaping Unitary's future. Contribute full-stack development, including software engineering, DevOps, and … are happy to get stuck into whatever needs doing, and are ready to learn and grow with the company. For this particular role, we need a proactive AI and machine learning expert who is familiar with leveraging and creating AI capabilities and who is comfortable engaging with customers and exploring and presenting new ideas. Strong communication skills are More ❯

for integrations, asyncio for concurrent processing, and building robust automation scripts with proper logging, testing (pytest), and documentation. AI & Machine Learning Frameworks - Deep expertise in AI/ML frameworks including TensorFlow, PyTorch, Scikit-learn, and Hugging Face Transformers. Experience building, training, and deploying machine learning models for classification, regression, clustering, and NLP tasks. Understanding of model … SQL Server), data validation, cleansing workflows, scheduling tools (Azure Data Factory), and ensuring data quality for machine learning applications. Machine Learning Operations (MLOps) - Experience deploying ML models to production environments using containerisation (Docker), orchestration (Kubernetes), model versioning (MLflow, DVC), monitoring model performance and drift, A/B testing frameworks, and implementing CI/CD pipelines for … model training and deployment. Understanding of model governance, explainability, and compliance requirements. Solution Architecture & Technical Design - Ability to design end-to-end automation architectures that combine multiple technologies (BPA, ML, GenAI, APIs) into cohesive solutions. Experience creating technical design documents, system architecture diagrams, assessing build vs. buy decisions, estimating effort and complexity, and presenting technical recommendations to both technical and More ❯

The Role Reporting to the Machine Learning Lead, youll be a hands-on Machine Learning Engineer with a strong track record of building and deploying ML solutions at scaleparticularly in NLP and GenAI. You will: Design, develop and scale NLP and GenAI capabilities to optimise business processes. Build out a robust GenAI application technology stack, from … experimentation through to production. Develop, maintain and improve existing ML pipelines, data transformation workflows and MLOps practices. Create serverless data/ML pipelines in cloud environments (Azure preferred). Work closely with architects, senior developers, product owners and business analysts to shape requirements, solution design and architecture. Own user stories end-to-end, contribute to sprint planning, and provide accurate … estimates for delivery. Translate business problems into well-structured ML and automation solutions using data-led insight. Collaborate with wider technology teams to share knowledge, improve processes, and produce training/documentation. The Person Were looking for someone who combines strong engineering fundamentals with practical ML delivery experience, and who enjoys working collaboratively in agile teams. Youll bring: Strong Python More ❯

visibility projects that directly influence the experience of millions of users. Youll collaborate with a diverse group of engineers, analysts, and product managers to design, build, and deploy scalable ML solutions that personalize and optimize search results across Expedias brands. In this role, you will: Research, design, and implement advanced ML and GenAI models for large-scale ranking and personalization. … Build, test, deploy, and iterate on ML models in production with measurable impact, validated by robust experimentation (A/B tests and online metrics). Combine state-of-the-art ML (deep learning, representation learning) with proven approaches (learning to rank, collaborative filtering). Collaborate cross-functionally with engineers, data analysts, and product partners to deliver robust … scalable, and impactful solutions. Stay abreast of advances in ML, GenAI, and academic research to infuse innovation. Technologies and tools you will use and own: PyTorch & TensorFlow: for large-scale development and training of deep learning models. Spark/Distributed Systems: for large data processing and model training at scale. A/B Experimentation Platforms: design, monitor, and analyze More ❯

visibility projects that directly influence the experience of millions of users. Youll collaborate with a diverse group of engineers, analysts, and product managers to design, build, and deploy scalable ML solutions that personalize and optimize search results across Expedias brands. In this role, you will: Research, design, and implement advanced ML and GenAI models for large-scale ranking and personalization. … Build, test, deploy, and iterate on ML models in production with measurable impact, validated by robust experimentation (A/B tests and online metrics). Combine state-of-the-art ML (deep learning, representation learning) with proven approaches (learning to rank, collaborative filtering). Collaborate cross-functionally with engineers, data analysts, and product partners to deliver robust … scalable, and impactful solutions. Stay abreast of advances in ML, GenAI, and academic research to infuse innovation. Technologies and tools you will use and own: PyTorch & TensorFlow: for large-scale development and training of deep learning models. Spark/Distributed Systems: for large data processing and model training at scale. A/B Experimentation Platforms: design, monitor, and analyze More ❯

in office) Up to £120,000 Shares + Benefits A fast-growing Data & AI Product-based company at the forefront of cutting-edge AI solutions are looking for an ML Lead to join the team and spearhead a number of ambitious products, shaping the architecture, direction, and delivery of advanced AI and Machine Learning initiatives. What youll do … Lead the design and development of Agentic AI systems, generative models, and NLP-powered solutions. Guide and manage a small talented ML engineering team, fostering innovation and technical excellence. Collaborate with product, data science, and engineering teams to bring state-of-the-art research into production. Evaluate and implement the latest AI frameworks, libraries, and cloud tools. Champion best practices … in model deployment, evaluation, and optimisation. What were looking for Strong track record in ML leadership, ideally in production-scale AI systems. Expertise in Agentic AI, LLM-based architectures, NLP techniques, and generative AI models. Solid programming skills (Python preferred) and experience with ML frameworks such as PyTorch, TensorFlow, Hugging Face. Hands-on experience with prompt engineering, fine-tuning LLMs More ❯