208 jobs for “Machine Learning Engineer cambridge”
VIQU IT London £75,000 – £80,000 pa
Designs and deploys AI/ML models for forecasting, propensity, churn and customer segmentation, owning end-to-end workflows from feature creation to ML Ops deployment and monitoring. Works hands-on across multiple products, architecting bespoke datasets and coaching junior data scientists in a cloud-native, AI-first SaaS team.
Wayve London
Works at the boundary between onboard software and vehicle hardware, bringing up new vehicle platforms on benches, HiL systems and vehicles, including at international test locations. Builds and maintains vehicle-facing components and shared frameworks in C++, Python or Rust on Linux-based robotic and automotive systems using ROS2, CAN and Automotive Ethernet, with diagnostics, tooling and documentation for long-term supportability.
Wayve London
Lead the technical architecture and roadmap for onboard localisation, designing and productionising state-estimation systems that fuse GNSS, IMU and wheel odometry for accurate vehicle pose estimates. The role spans algorithm design, prototyping, validation and deployment on real-time vehicle platforms, with hands-on technical leadership and mentorship across robotics, calibration, controls and sensor teams.
Relation Therapeutics London
Design and implement generative models that learn intervention effects from single-cell perturbation and multiomic data, focusing on counterfactual prediction, generalisation and experimental design. Work in interdisciplinary teams with experimental biologists to validate computational hypotheses and guide the highest-signal next experiments, using modern ML tooling including agentic workflows.
University of Sheffield Sheffield £32,080 pa
Build and evaluate machine learning models that predict Strep A outbreak risk from multiple real-world datasets, turning them into early-warning signals. Work with clinicians and an engineering team so analyses feed into a practical public health tool, with a focus on reproducible Python and/or R analysis.
University of Oxford Oxford £49,119 – £59,955 pa
Leads a research strand on Bayesian methods for evaluating and monitoring AI systems, publishing findings, running the lab's open-source software, producing policy-facing outputs, and guiding research assistants and students. Based in the Bayesian Governance Lab within Oxford's Department of Engineering Science, in collaboration with the Oxford Martin AI Governance Initiative, on a two-year fixed-term post.
University of Sheffield Sheffield £39,560 – £43,099 pa
Postdoctoral role applying explainable NLP and machine learning to analyse online disinformation narratives, integrate findings into a user-facing verification toolkit, and evaluate commercial chatbots and AI-generated search overviews. The researcher joins the European-funded ANTIGONE project, collaborating with multidisciplinary partners and leading publication of results in high-impact journals and conferences.
University of Exeter Exeter £21,805 pa
An interdisciplinary PhD co-designing miniaturised, low-power sensing hardware with AI for field-based wildlife monitoring, including individual recognition and automated behaviour quantification. Systems are benchmarked in controlled conditions then validated on wild jackdaws and West African field sites, spanning behavioural ecology, electronic engineering and data science.
University of Exeter Exeter £21,805 pa
Develop next-generation machine learning models to predict genetic interactions from large-scale perturb-seq data, evaluating graph neural networks and autoencoders for genome-wide scalability. The purely computational project feeds a lab-in-the-loop cycle with pancreatic cancer screens from the AstraZeneca and Cancer Research Horizons Functional Genomics Centre, with results released as open-source software.
University of Oxford Oxford £39,424 – £47,779 pa
Develops novel statistical and machine learning methods for large-scale genomic, phenotypic and health data, covering areas such as genomic language models, multimodal and federated learning, and multi-ancestry methods. Builds scalable, reproducible research software applied to biobank-scale datasets, evaluates statistical and predictive performance, publishes findings and guides junior researchers in the Palamara Group.
University of Cambridge Cambridge £63,606 – £67,468 pa
The role involves contributing to research and teaching in artificial intelligence and machine learning, with a focus on fundamental ML, novel models and architectures. The appointee will develop graduate content for the MPhil in Advanced Computer Science, contribute to undergraduate teaching, and build a research team supported by external funding.
University of Surrey Guildford £21,805 pa
Develops next-generation federated machine unlearning algorithms that deliver verifiable, robust erasure without harming model performance or participant privacy. Research spans certified unlearning with formal guarantees, robustness to adversarial relearning, federated-specific benchmarks, and scalable unlearning for foundation models, supervised by Dr Pedro Porto Buarque de Gusmao and Dr Frank Guerin.
Isomorphic Labs London
Join the Computational Sciences team to design novel large-molecule therapeutics using a cutting-edge AI drug design engine. You'll develop machine learning methods to predict biologics properties from sequence, benchmark models, and analyse lab data to guide early discovery through candidate selection.
Isomorphic Labs London
Lead all externalised drug discovery and preclinical lab operations, building and scaling a global CRO infrastructure for an AI-first drug design platform. Oversee experimental throughput, data QC and turnaround times, embed data-generation-by-design standards with Data Engineering, and manage vendor governance, budgets and a team of CRO Scientific Leads, Operations Managers and Compound Managers.
University of Surrey Guildford £21,805 pa
Develops a computational framework combining computer vision, graphics and machine learning to speed up and improve cinematic camera lens design and simulation. The work covers forward simulation of candidate lens configurations and inverse design of lens architectures against imaging or perceptual objectives, using differentiable rendering and data-driven models. Based at the Vision, Speech and Signal Processing group under Dr Marco Volino and Dr Jean-Yves Guillemaut, with close industry collaboration.
