228 jobs for “Machine Learning Engineer cambridge”
Darktrace Cambridge
Conducts independent and collaborative research across large language models, statistical methods and classical machine learning, prototyping ideas and implementing models into the wider software stack. Produces optimised solutions for latency and memory, including deployment on edge devices, working closely with software engineers and security analysts.
PhysicsX Singapore
Lead the deployment of ML models and engineering surrogates—deep learning on CAE/CFD/FEA data, time-series forecasting, anomaly detection, and optimisation—into customer production environments. Own scoping, architecture, and success metrics for data/ML systems built with Python, PyTorch, Pandas, fastAPI, Scipy, and Kubeflow across cloud and on-prem. Mentor engineers and data scientists while travelling 3-4 weeks per quarter to customer sites worldwide.
Wayve London
Train, debug and improve computer vision and 3D perception models for driver assistance, working across the full ML lifecycle from data and training to evaluation and iteration. The role spans latency-constrained on-car perception and large-scale offline work with lidar, maps and 3D reconstruction to build auto-labelling data flywheels.
Wayve London
Lead large-scale data enrichment and curation for the Core Model Safety team, mining hard and rare events and building workflows across pre/mid-training, reward modelling and self-supervised labelling. Design and train out-of-distribution detection mechanisms for robust driverless operation, working at the intersection of model engineering, infrastructure, compute and data.
Faculty London
Set technical direction for complex AI/ML projects, leading delivery of large-scale platforms in high-risk national security environments. Define roadmaps across multiple workstreams, justify architectural decisions to senior stakeholders, and coach engineers while building shared deployment and CI/CD infrastructure. Requires DV eligibility and occasional on-site client work.
Faculty London
Serve as a high-level technical authority steering the most complex AI projects, architecting scalable large-scale systems and setting technical direction for flagship initiatives. Provide authoritative advice across business units, influence company-wide technical strategy, and act as a respected expert for internal teams and external customers in the financial services space.
WeDoTech London £120,000 – £160,000 pa
Hands-on technical leadership role building and scaling enterprise Generative AI, LLM and agentic AI systems across multiple engineering teams. Involves designing production-grade RAG and multi-agent solutions, shaping reusable AI frameworks and standards, and ensuring reliability and governance in a regulated financial services environment.
ARM Dublin, Ireland
Lead the architecture, deployment and operation of a large-scale AI/ML platform spanning conventional ML and agentic AI, owning the roadmap and engineering standards. Hands-on role covering MLOps/LLMOps, CI/CD, IaC, Azure infrastructure and multi-agent orchestration frameworks, while mentoring engineers and acting as senior escalation point.
Ocado Kraków, Poland
Senior ML engineer role in a cross-craft data science team building prediction, ranking and personalisation systems for an e-commerce platform. Owns the full ML lifecycle on production systems, from experimentation and training through serving, monitoring and MLOps, while coaching others and shaping reusable platform building blocks.
eFinancialCareers London
Design and build AI-powered tools, automations and integrations using Python, PowerShell and APIs, exploring Agentic AI and LLM use cases across internal business functions. Advise on embedding AI into enterprise architecture within a regulated investment management environment, working with engineering, product and business teams. Distinct for its focus on engineering productivity and architecture strategy rather than traditional ML modelling.
Relation Therapeutics London
Builds and scales generative and predictive models of cellular behaviour, implementing and optimising large neural networks and distributed training infrastructure. Acts as a bridge between ML research and production, profiling GPU workloads and optimising inference for use by data scientists and biologists on multi-modal biological data.
MFK Recruitment Brentford £70,000 – £95,000 pa
Design and deploy production-grade computer vision systems using deep learning techniques such as CNNs and Vision Transformers, translating research into robust AI solutions for defence and security applications. Work across the full development lifecycle, from model design and training to deployment on cloud and edge platforms. Collaborate with researchers, engineers, and customers in a technically challenging environment focused on real-world autonomy and perception systems.
NVIDIA Cambridge
Develops algorithms and optimizations for NVIDIA's LPX inference and compiler stack, building high-performance runtime and compiler components for end-to-end inference. Involves mapping large-scale neural network workloads onto future hardware, working with LLVM/MLIR, and collaborating with hardware architects on codesign. Hybrid role based in Cambridge.
NVIDIA United Kingdom
Develops algorithms and optimizations for NVIDIA's LPX inference and compiler stack, building high-performance runtime and compiler components and mapping large-scale inference workloads onto future hardware. Works at the intersection of compilers, systems and deep learning, using LLVM/MLIR and frameworks like PyTorch and TensorFlow, and collaborates with hardware architects on codesign.
Latent Labs London
Architect novel generative models to design functional proteins, working in an interdisciplinary team of ML researchers, protein engineers and biologists. The role spans data curation, evaluation metrics, rapid prototyping, cloud training and inference, and planning wet lab testing campaigns, with about 10% of time for self-development.
