Machine Learning Jobs

• London
• On-site
• Mid-level · manages people
• Permanent

Join the Preparedness team to anticipate and mitigate loss-of-control risks from increasingly capable AI systems, potentially culminating in recursive self-improvement. The role spans scalable oversight, automated auditing, monitorability testing, model behaviour science, and coordination/verification mechanisms, alternating between rigorous hypothesis-driven research and building interventions that impact production models.

• London
• On-site
• Mid-level
• Permanent

Researcher role focused on derisking frontier AI models by developing novel safety mitigations, drawing on interpretability, control, and alignment techniques. You will build and refine evaluations of emerging risks, design red-teaming pipelines, and set research directions, collaborating closely with experts in misalignment, cybersecurity, and biology.

• London
• Hybrid
• Mid-level
• Permanent

Builds and deploys production-grade machine learning systems for national security and AI safety clients, including LLM applications, multi-agent tooling and evaluation of frontier models. Involves leading technical scoping and architecture decisions, defining deployment standards, and advising customers while working alongside engineers, data scientists and commercial leads.

AWS · Azure · GCP +5

• London
• Hybrid
• Senior
• Permanent

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.

TensorFlow · PyTorch · AWS +4

• Brentford
• Hybrid
• £70,000 – £95,000 pa
• Senior
• Permanent

Hands-on role designing and deploying production computer vision systems using CNNs and Vision Transformers, from model architecture and training pipelines to optimisation for cloud and edge. Works alongside software engineers, researchers and customers, translating recent AI research into reliable products for defence and security environments.

PyTorch · TensorFlow · Git +6

• Butterrow
• £55,000 – £65,000 pa
• Mid-level

Designs and builds real-time embedded software in C and C++ for microelectronics and sensors, alongside data pipelines and machine learning systems. The role covers CI/CD for ML, model versioning and drift monitoring, generative AI and LLM work including RAG and fine-tuning, plus ETL/ELT pipelines and IoT data services. Joins a small team owning the full SDLC from clean-sheet design to live deployment.

Spark · dbt · CI/CD +1

• London
• £23,805 pa
• Entry level
• Contract

Develop a framework combining a differentiable reacting flow solver with a machine learning-based controller to anticipate and mitigate extreme events such as flashback and thermoacoustic instabilities in hydrogen and SAF combustion. The role sits within the European CONTEXT project at the intersection of scientific machine learning and fluid dynamics, using high-fidelity simulations and Imperial's HPC facilities.

HPC

• Oxfordshire
• Hybrid
• £60,000 – £94,000 pa
• Senior

Lead technical development of computer vision, perception and autonomous navigation systems, covering algorithm design, subsystem architecture, verification and deployment. Work spans object detection, tracking, 6DoF pose estimation, LiDAR and camera integration, HIL testing and embedded/flight software, with mentoring of less experienced engineers across multidisciplinary teams.

OpenCV · TensorFlow · PyTorch +5

• London
• Senior
• Permanent

Design and implement generative models that learn intervention effects from single-cell perturbation and multiomic data, focusing on counterfactual prediction 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 and scalable infrastructure.

• United Kingdom
• Entry level
• Internship

Six- to twelve-month AI and algorithms internship for PhD or Master's students, working alongside engineers on client projects involving modelling, training, testing and data wrangling. Interns also contribute to internal R&D, building on state-of-the-art AI literature, and present results to colleagues and clients. Requires strong Python, Git and demonstrable research experience, plus UK security clearance eligibility.

Git · Transformer Models · Diffusion Models +1

• United States
• Remote
• US$180,000 – US$200,000 pa

Develop and improve production machine learning systems, designing, building and deploying models used in high-volume environments. Own experimentation frameworks and evaluation methodologies, research new techniques, and work with large-scale distributed data platforms using Spark and Python/SQL. Partner with Product and Engineering to translate business problems into data-driven solutions.

Spark

• Cambridge
• Mid-level

Hands-on compiler engineering focused on kernel generation and computational graph optimizations for next-generation NVIDIA GPUs, solving complex compilation problems for AI inference and training workloads. Works with MLIR, C/C++ and Python, collaborating with software, hardware and research teams on hardware/software co-design and datacenter-scale AI deployment.

MLIR · GPU · CPU +1

• London
• Senior
• Permanent

Processes and QC's paired single-cell RNA-seq and scATAC-seq at scale, building Nextflow pipelines and multimodal training datasets in Zarr for GPU-accelerated model training. Partners with wet lab scientists and ML modellers, contributing to evaluation frameworks that test whether models capture meaningful biology.

STARsolo · Alevin-fry · Chromap +7

• Exeter
• £21,805 pa
• Entry level
• Contract

Develops a multiscale Scientific Machine Learning digital-twin framework to predict thermal trajectories, torque capability and efficiency in low-speed, high-torque electric propulsion. Combines physics-informed neural networks, neural state-space models and Neural ODEs, validated through safety-constrained dynamometer experiments at the Centre for Future Clean Mobility and on-site work with a marine power-systems partner.

Neural Ordinary Differential Equations · Deep Neural Networks · Recurrent Neural Networks +1

• Exeter
• On-site
• £21,805 pa
• Entry level
• Contract

A fully funded PhD studentship researching how small language models can become reliable agents for bounded business workflows, using harness optimisation and fine-tuning on traces from larger teacher models. The work measures reliability, cost, latency and data locality, and releases open tooling for UK SMEs, in collaboration with an industry research lab.

Large Language Models