213 jobs for “Machine Learning Engineer cambridge”
Faculty London
Drives technical strategy, architecture and deployment of secure AI systems across high-stakes domains, bridging AI research and production. Leads capability testing for Frontier AI models, builds scalable ML infrastructure and multi-agent tooling, and advises senior client stakeholders while mentoring engineers.
Faculty London
Lead the design, build and deployment of production-grade ML and LLM systems for national security and AI safety clients, including capability testing of frontier models. Act as a trusted technical advisor, define engineering standards for ML at scale, and mentor junior engineers while working with frontier labs on red teaming and evaluation.
Wayve London
Sets technical strategy and roadmap for fault detection and fallback systems in an autonomous driving stack, designing and training detection mechanisms for robust driverless operation. Leads integration into the shared driving stack, aligning ML, inference optimisation and software teams, and mentors through architecture reviews. Works with large-scale training and fleet data in a small, high-impact team.
Wayve London
Builds virtual vehicle models using physics-based and data-driven techniques, validating them against on-road data and converting them into efficient software components. Runs track and partner experiments to improve model accuracy, and integrates models into simulation, hardware-in-the-loop and correlation pipelines across robotics and product teams.
Thought Machine London
Guardian of mission-critical production infrastructure powering core banking and payments platforms for major financial institutions. Involves automating fleet management, designing disaster recovery and capacity planning, participating in a global on-call rotation, and mentoring engineers while working with senior stakeholders and SaaS customers.
Thought Machine London
Technical Programme Managers own the delivery of complex, multi-team engineering programmes, from planning and milestones through to coordination and stakeholder communication. The role requires hands-on understanding of microservice stacks such as Kubernetes, Kafka and AWS/GCP, and involves driving continuous improvement across a fast-paced engineering organisation.
University of Exeter Exeter £21,805 pa
Develops a multiscale Scientific Machine Learning digital-twin framework to predict thermal trajectories, torque capability and efficiency in low-speed, high-torque electric propulsion under extreme duty cycles. Combines physics-informed hybrid architectures (DNNs, neural state-space models, Neural ODEs) with safety-constrained dynamometer experiments at the Centre for Future Clean Mobility, in collaboration with marine power-systems company Ecomar Innovations.
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 Hertfordshire Hatfield £39,560 – £46,970 pa
Postdoctoral role delivering research on innovative AI/ML algorithms for predictive modelling and optimisation of agricultural applications from heterogeneous data, as part of an Innovate UK-funded collaborative project. Involves developing AI/ML software tools, data management and analysis, supporting the Principal Investigator on project milestones, and contributing to publications and reports.
UCL London £46,261 – £48,679 pa
Develop and evaluate novel AI algorithms to quantify brain iron load from standard-format MRI data, with a focus on quantitative susceptibility mapping (QSM). Based in UCL's Hawkes Institute, a multidisciplinary grouping at the intersection of engineering and health, within a top-ranked computer science department.
The University of Manchester Manchester £48,337 – £59,390 pa
Develops and applies machine-learning and AI methods to protein engineering and enzyme design, analysing large biological, chemical and experimental datasets and building predictive models and computational tools. Works within an interdisciplinary group spanning the Manchester Institute of Biotechnology and Department of Chemistry, providing ML and data-science expertise, training and support to postdocs and students, and contributing to publications and funding bids.
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.
Capital One Loughborough
Lead the development of proprietary deep learning models to enhance underwriting capabilities, building neural networks such as LSTMs, RNNs and Transformers on structured and unstructured data. Set technical direction, manage projects, communicate with stakeholders and mentor junior team members, taking ideas from prototype to production in a hybrid Nottingham team.
Capital One Lincoln
Lead the development of proprietary deep learning models to enhance underwriting capabilities, building neural networks such as LSTMs, RNNs and Transformers on structured and unstructured data. The role involves setting technical direction, mentoring junior team members, and driving prototypes through to production in collaboration with business stakeholders.
