392 jobs for “Machine Learning Engineer”
PhysicsX Singapore
Customer-facing engineering role building and deploying applications that put physics AI models into production for industrial clients. You will work directly with customers, data scientists and ML engineers, prototyping tools, iterating on user feedback, and building Python FastAPI microservices deployed on Kubernetes, Terraform and AWS/Azure.
PhysicsX Singapore
Join a new Singapore research team building physical foundation models for industrial engineering, translating physics challenges into mathematical formulations and training deep learning models on large datasets. You will own research workstreams, run experiments, and communicate results to customers and at publication venues, with a focus on operator learning, geometric deep learning, or generative models for geometry and spatiotemporal data.
Back TO Work South Shields £25,900 pa
An early-career role building an AI Agent for an educational software support company, covering data preprocessing, exploratory analysis, model fine-tuning and implementing machine learning algorithms. The position works with cross-functional teams to define requirements and deliver scalable solutions, and is aimed at someone new to the industry with no prior experience required.
Harnham - Data and Analytics Recruitment London £75,000 – £85,000 pa
Owns the infrastructure, deployment and operational excellence of production machine learning systems within a growing AI and data organisation serving the public sector. Builds ML orchestration pipelines with Dagster, Airflow or Prefect, runs Kubernetes and Terraform/Bicep infrastructure, and maintains CI/CD and observability for models and LLM-powered solutions, working closely with data scientists and client-facing teams.
Rise Technical Recruitment London £90,000 – £120,000 pa
Design and build full-stack AI-powered product features, working across front-end, back-end, AI and infrastructure. Develop and optimise LLM, computer vision and agent-based systems, plus evaluation, prompt engineering and fine-tuning frameworks. High-ownership role shaping product direction and AI strategy in a scaling financial crime prevention start-up.
NVIDIA Switzerland
Develops performance optimizations in deep learning frameworks using JAX, contributing to JAX core components and driving peak performance on NVIDIA hardware. Works with AI researchers to build future-proof models and tooling that bridges numerical computing, simulation and deep learning research. Requires C/C++ and Python skills plus deep knowledge of ML framework internals and CPU/GPU architectures.
NVIDIA United Kingdom
Develops performance optimizations in deep learning frameworks using JAX, contributing to JAX core components and driving peak performance on NVIDIA hardware. Works with AI researchers to build future-proof models and tooling that bridges numerical computing, simulation and deep learning research. Requires C/C++ and Python, ML framework internals, and CPU/GPU architecture expertise.
Isomorphic Labs London
Join the model performance and scaling team to implement and optimize LLM post-training methods on frontier models, collaborating with research teams to turn new methods into production-ready systems. The role focuses on distributed training and inference performance, low-precision methods, and frameworks like JAX or PyTorch, in a hybrid London setting.
Adria Solutions Huddersfield £35,000 – £45,000 pa
Supports AWS infrastructure, CI/CD pipelines and automation for software and machine learning workloads, including packaging, versioning and deploying ML models. Works alongside software and AI engineers to keep development, testing and production environments consistent, monitoring pipelines and fixing issues. Suited to an early-career engineer with cloud, scripting and Git foundations and an interest in MLOps.
Ncounter Manchester £80,000 – £90,000 pa
Hands-on research engineering role investigating the internal behaviour and security of large language models, turning academic ideas into practical experiments in Python. Work spans model internals, data movement, training risk and safe deployment, alongside production-quality ML engineering, testing and code reviews. Requires active SC clearance and around three days per week on secure sites.
HAYS Specialist Recruitment London £70,000 – £90,000 pa
Designs and builds modern machine learning and AI services within a collaborative data team, developing and optimising data pipelines across a cloud analytics platform. Works with PySpark, Python, SQL, Databricks or Snowflake on AWS, plus Airflow, Terraform, Docker and Kubernetes, in agile squads supporting ML and GenAI infrastructure.
Tech Recruitment Specialists Ltd London £37,000 – £40,000 pa
Join a two-year graduate programme in the telecommunications industry, developing and implementing AI and machine learning solutions for network performance, operational efficiency and customer experience. You will work with Python and AI frameworks, analyse large datasets, and collaborate with engineers and data specialists while considering AI ethics and governance.
Wayve London
Owns the technical vision and architecture for a platform that lets model engineers deploy, run, evaluate and improve ML models over petabytes of driving data and large GPU fleets. Combines hands-on backend engineering in Python with cross-team technical leadership, mentoring senior engineers and leading a small team of 2-3.
Ocado London
Owns the software engineering that brings data science and machine learning products into live production for the Autoplanner team, building AI-powered planning systems across global warehouses and last-mile assets. Writes typed, well-tested Python (with some Java for OSP integration), builds APIs and data contracts, manages AWS deployments and CI/CD, and packages, serves and monitors ML models. Acts as engineering partner to data scientists and shares on-call support.
OpenAI London
Designs, builds and maintains production harm-detection systems using SQL, Python, machine learning and language models, developing signals, classifiers and pipelines on shared engineering platforms. Also owns protection strategy and cross-functional delivery for a harm area or product launch, connecting detection with policy, review, enforcement and measurement, and participates in an on-call rotation.
