5,576 to 5,600 of 6,657 Machine Learning Jobs in the UK

technically leading security engineers Familiarity with digital engineering, model-based systems engineering or requirements-management tools Experience working with or familiarity with AI/ML models is preferred Additional Information This role has a salary of between 59,200 and 80,000 plus our flexible benefits package. We are open ...

technical roadmaps aligned with growth roadmaps and long-term defence strategiesevaluating and selecting technologies across cloud, edge computing, secure networks, data platforms, AI/ML, and mission critical softwareCollaborating with senior military users, programme managers, and engineering leads to capture operational needs and translate them into technical solutionsBeing responsible ...

equivalent threat modelling methodologies (STRIDE, PASTA) applied to embedded or OT/IT convergent systems. Understanding of secure‐by‐design principles for AI/ML‐enabled systems, including securing inference pipelines, model integrity, and cloud‐to‐edge communication paths. Exposure to CAN bus, Ethernet backbone, or wireless interface security ...

Nice-to-Haves Experience with analytics, monitoring or observability tooling Background in automotive, marketplaces, or high-SKU B2B platforms Exposure to AI/ML-powered products or startups Prior experience leading UI best practices or mentoring engineers This Role Is NOT For You If You prefer remote work — this role ...

commercial teams as the technical lead for high-value AI infrastructure opportunities. Engage directly with customer CTOs, Chief AI Officers, infrastructure leads, and ML engineers to evaluate technical requirements, compute sizing, and fabric choices. Lead deep-dive architectural workshops and technical presentations on Civo's bare-metal GPU and managed ...

delivery experience with international public-sector or similarly regulated customers, bridging regional technical teams and senior stakeholders.- Have successfully led GenAI or traditional ML implementations for government agencies in close collaboration with systems integrators and implementation partners.- Understand network and cloud architecture, including on-premise deployments, and show practical judgment ...

building, and delivering software or AI systems in enterprise environments, including taking systems from prototype to production. Relevant backgrounds may include applied AI or ML engineering, forward‐deployed engineering, software engineering, developer tooling, customer engineering, solutions architecture, or technical consulting. Can point to substantial personal contributions in code, architecture, evaluation ...

atmosphere Competence leveraging value selling frameworks such as Command of the Message and forecasting methodologies such as MEDDPICC Preferred: Experience selling to AI/ML leaders and builders Wondering if you’re a good fit? We believe in investing in our people, and value candidates who can bring their ...

AI100. At Basecamp Research, we pride ourselves on being a lean collaborative and global team with extremely specialist and unique skills. Our biologists, engineers, ML scientists and field explorers are united by a sense of adventure and the belief that AI, biology and data, will result in new medicines ...

distributed systems Strong knowledge of Kubernetes, networking technologies, security practices, and enterprise storage systems Hands‐on familiarity with distributed cloud-native and AI/ML workloads on GPU‐based computing at scale Exceptional ability to lead, inspire, and develop high-performing teams, building an environment of trust and excellence Excellent ...

Data Practice Lead | £120-140k | Build a Standalone Data Practice | London G.Digital has exclusively partnered with a world-class technology consultancy as they establish a brand-new Data Practice. Known for delivering bespoke software ...

Great ideas come from different minds. That’s why we bring together engineers, scientists, analysts, and creatives from every background — and give them the trust, tools, and freedom to make a difference. What connects us ...

Roke, 5th Floor, Space, Woking, Surrey, United Kingdom Job Description Posted Friday, 27 February 2026 at 01:00 Great ideas come from different minds. That’s why we bring together engineers, scientists, analysts, and creatives ...

make in your first year become the ecosystem the team builds on. What we look for Six years or more building and shipping ML systems that customers used and that you were responsible for end-to-end, from offline metric to user-visible behaviour. Strong on at least … federated or edge ML systems; evaluation and orchestration; simulation-based testing and benchmarking; compiler-style configuration systems, or anything in that family. An instinct for making things simpler alongside making them more capable. We hire people who reduce complexity, not just add to it. Comfortable in both owning a multi ...

world and synthetic training data. Bridge research and application engineering so model improvements actually reach users. The bar Read this before you DM. Production ML systems you've built and shipped — not prototypes, not research demos, real products with real users Deep understanding of large-model training, fine-tuning, evaluation … inference Experience running GPU-based ML workloads at meaningful scale Strong software engineering fundamentals — you write production-grade code and you care about correctness Comfortable reasoning about failure modes, model degradation, and what happens when things go wrong in the wild Independent judgment — you can navigate ambiguity and make pragmatic ...

DoYou will work with our team of applied research engineers at the intersection of computer vision, gameplay agents, natural language processing, and machine learning to create state-of-the-art tools to support game developers in our ecosystem with a focus on bots (trained gameplay agents, intelligent NPCs … open weights modelsReinforcement learning, incl. experience with agentic systems, reward design, policy optimisation, evaluation, and building scalable training environments for agentsPython and associated ML tools/frameworks (numpy, scipy, sklearn, pytorch)Experience with working collaboratively with other developers, following a flexible/agile/lean approachEPIC JOB + EPIC ...

delivery — this is your chance to shape the intelligence behind the future of work. Join RoleMapper and lead the evolution of our AI and ML capabilities that make workforce decisions fairer, smarter, and more transparent. About RoleMapper In a world where organisations are facing significant skills challenges, increasing compliance requirements … phase of growth and position RoleMapper at the forefront of AI in work design. Responsibilities Translating product vision into a feasible, scalable AI and ML roadmap that delivers measurable business value and aligns with commercial goals. Designing and scaling RoleMapper’s AI and Machine Learning models, combining leadership ...

proposing fixes. Apply optimisation techniques (e.g., quantisation and distillation where beneficial), understanding trade-offs and when methods are appropriate. Collaborate cross-functionally with adjacent ML and performance engineering teams to hand off models, define bottlenecks, and align on optimisation priorities. Communicate clearly with stakeholders to align on delivery timelines, trade … Experience working on models that must meet tight latency/efficiency constraints (edge, embedded, real‐time, or similarly constrained production settings). Exposure to ML systems spanning training → evaluation → deployment handoff (even if you’re not writing kernels day‐to‐day). Exposure to embedded or edge deployment of ML ...

proposing fixes. Apply optimisation techniques (e.g., quantisation and distillation where beneficial), understanding trade-offs and when methods are appropriate. Collaborate cross-functionally with adjacent ML and performance engineering teams to hand off models, define bottlenecks, and align on optimisation priorities. Communicate clearly with stakeholders to align on delivery timelines, trade … skills. DesirableExperience working on models that must meet tight latency/efficiency constraints (edge, embedded, real-time, or similarly constrained production settings).Exposure to ML systems spanning training evaluation deployment handoff (even if you're not writing kernels day-to-day).Exposure to embedded or edge deployment of ML models ...

Описание: The company is a leading technology innovator focused on developing cutting-edge AI and machine learning solutions for various industries. Задачи: Develop, train, and optimise advanced computer vision and machine learning systems Deploy solutions in constrained edge environments Collaborate with cross-functional teams on project … delivery Contribute to the full lifecycle of machine learning model development. Требования: Proven experience as a Machine Learning Engineer Expertise in computer vision and machine learning techniques Experience with deploying models in edge environments Strong programming skills in relevant languages (e.g., Python) Ability ...

Staff Machine Learning Engineer – Ads Bidding The TeamThe Ads ML team builds and maintains the machine learning models powering the company's advertising product — connecting consumers with relevant ads and helping merchants, grocers, and FMCG brands grow through the platform. The UK team is ~11 MLEs … baseline — you'll be setting direction in an ambiguous space, not executing against an established one 7+ years writing production code in Python; solid ML fundamentals in ranking, recommendation systems, or bidding/auction systems A bias for simplicity and a focus on shipping work with measurable business impact Strong ...

real vehicles. Getting our models onto embedded hardware — correctly, quickly, and reproducibly — is one of the hardest problems between research and product. As a ML Compiler Engineer, you will own the compilation pipeline that makes that possible. You will build and extend Wayve's ML compiler end-to-end: designing … graph. Your work spans the full lowering stack, building compiler passes and infrastructure that scale across architectures and target platforms. Key responsibilities Own the ML compilation pipeline end-to-end — from checkpoint to deployable bundle on NVIDIA (TensorRT) and Qualcomm (QNN) targets. Design and implement compiler passes with accuracy ...

looking for strong C++ software development experience , ideally gained while building machine learning inference engines, runtime systems, or backend integration frameworks. Experience working with a machine learning inference framework such as LiteRT, TensorFlow Lite, ONNX Runtime, or a similar technology is also important. A good understanding ...

good fit if you Have strong software engineering fundamentals and a track record of building performant, reliable systems Have worked on ML infrastructure, distributed systems, or research tooling Care about enabling other people's work and find leverage through platforms rather than individual experiments Are comfortable operating across the stack … Strong candidates may also have Experience with large-scale distributed training (RL, pre-training, or post-training) Familiarity with JAX, PyTorch, or similar ML frameworks A track record of operating at the edge of research and infra in a fast-moving environment Compensation Annual Salary ...

across the firm. Take the next step in your career. Responsibilities We are looking for exceptional engineers to help us build out a mature ML research and deploy pipeline as part of our ML Workflows team. This is an exciting role. You will develop green‐field solutions to meet highly … complex ML interdependency requirements. Where off‐the‐shelf tools fall‐short, you’ll build custom solutions to define best practice across quantitative research. Future Projects Implementing best practice feature and model stores Properly versioning features, data and models Improving inference compute utilisation via model serving CI/CD for ML ...