92 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 Remote (UK)
Lead backend and edge/IoT engineering for high-stakes Defence projects, bridging proof-of-concept work and robust production systems. You will mentor a squad of engineers, design complex components, and build CI/CD and containerisation pipelines with Docker and Kubernetes while shipping Python and compiled-language code alongside ML engineers and data scientists.
Carrington Recruitment Solutions Leeds £80,000 – £90,000 pa
Hands-on full stack lead role guiding a small development team across a portfolio of applications, setting engineering standards and shaping delivery. Work spans C#, .NET, Python, Azure PaaS, SharePoint and React, with an AI-native edge using GenAI tooling. Mainly remote with occasional light travel to Leeds and other offices.
Carrington Recruitment Solutions Manchester £80,000 – £90,000 pa
Hands-on full stack lead role guiding a small development team across a portfolio of applications, setting engineering standards and shaping delivery. Works with C#, .NET, Python, Azure PaaS, SharePoint and React, collaborating with Product and Architecture, with an AI-native edge using GenAI tooling. Mainly remote with occasional Manchester office visits.
Wayve London
Lead the Applied Methods Data Science team, partnering with the Autonomy organisation to turn experimental and observational analysis of real and simulated driving into evaluations and insights. Set three-, six- and 12-month roadmaps, review technical proposals for statistical rigour, hire and grow data scientists, and build tooling to scale the team's capability.
Wayve London
Owns the technical architecture and roadmap for LiDAR and cross-sensor 3D sensing, developing calibration, registration, temporal alignment and motion compensation methods. Blends algorithm research with production deployment in C++/Python, providing technical leadership and mentorship across the 3D sensing stack.
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.
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.
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 Cambridge, United States
Lead DMPK strategy across drug discovery projects, designing screening cascades and mechanistic experiments while integrating PK, PD and toxicology data for dose and safety predictions. Work within an AI-first preclinical team, shaping ADME predictive models and authoring regulatory documents to advance candidates toward first-in-human trials.
Isomorphic Labs Cambridge, United States
Lead the safety assessment strategy for drug discovery projects from inception to regulatory submission, designing screening cascades and mechanistic experiments for small molecules and biologics. Partner with machine learning researchers to build predictive toxicology models and manage CRO relationships for outsourced wet-lab data generation, while mentoring junior scientists.
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.
