Artificial Intelligence Jobs

NVIDIA · United Kingdom

Engages directly with customers and partners to architect and validate large-scale GPU-accelerated HPC/AI clusters, spanning hardware handover through Day 2 production stability. Works tool-agnostically across upstream Kubernetes, KubeVirt, Slurm, Prometheus/Grafana and Cumulus/SONiC, owning burn-in testing, fleet reliability and enablement runbooks.

NVIDIA · Germany

Engages directly with customers and partners to architect and validate large-scale GPU/HPC clusters, owning full-solution validation and Day 2 production stability at fleet scale. Works tool-agnostically across upstream Kubernetes, KubeVirt, Slurm, Prometheus/Grafana and Cumulus/SONiC, acting as hands-on technical leader and trusted advisor for assigned accounts.

Faculty · Remote (UK)

Lead the design, build and deployment of production-grade ML systems for defence clients, covering architecture, scalable infrastructure and MLOps standards. Work cross-functionally with engineers, data scientists and commercial teams, acting as a technical advisor and mentoring junior engineers. Requires on-site work with customers 2-4 days per week and eligibility for UK Security Clearance.

Isomorphic Labs · Cambridge, United States

Lead medicinal chemistry on drug discovery projects from initiation to clinical candidate selection, either as Project Lead or Medicinal Chemistry Lead. Partner closely with ML scientists to refine the AI drug design platform, manage CRO resources, and generate IP. Some roles include line managing 2-4 chemists.

CrowdStrike · Ireland

Security researcher role on CrowdStrike Intelligence's Advanced Research Team, performing vulnerability research and exploit development across a wide range of targets. Day-to-day work includes analysing vendor patches, identifying exploits in large file collections, reverse engineering, and building automated data collection and analysis tooling, alongside publishing research and supporting other intelligence teams.

CrowdStrike · United Kingdom

Join the Advanced Research Team to conduct vulnerability research and exploit development, analysing vendor patches to identify vulnerabilities and build proof-of-concept exploits. The role also involves reverse engineering, investigating 0-day and n-day exploitation, and developing automated tooling to process and analyse data at scale, with results published on the blog or at conferences.

Wayve · London

You'll define and manage the technical architecture for integrating Wayve's AI Driver into OEM and Tier 1 vehicle platforms, covering software–vehicle interfaces, sensors, middleware, ECUs, timing, diagnostics and validation. The role sits between core AI architecture and customer programs, turning ambiguous requirements into interface contracts, ownership boundaries and verifiable specifications.

University of Exeter · Penryn · £21,805 pa

Develops physics-aware spatio-temporal graph neural networks for 0–6-hour visibility forecasting, focusing on low-visibility events in southeast England. The work spans six packages, from benchmarking NWP and ML baselines to linking learned representations with atmospheric physics, testing robustness to degraded observations, and operational evaluation with Met Office scientists.

Medtronic · London · £76,800 – £115,200 pa

Designs, benchmarks and optimises deep learning models for computer vision and surgical video understanding, focusing on low-latency inference on edge and cloud devices. Works with ML, platform and embedded engineers on end-to-end video pipelines, using PyTorch, TensorRT and techniques like pruning and quantization. Distinct for its operating-room, safety-critical medical imaging context.

University of Birmingham · Birmingham · £21,805 pa

Develops a physics-informed AI framework to design and optimise alternative cooling mechanisms and refrigeration cycles, integrating thermodynamic modelling, machine learning and multi-objective optimisation. Experimental work validates selected combinations, with scope to balance computational and lab effort. Based in the School of Chemical Engineering alongside sustainable cooling and energy storage research centres.

Helsing · London

Builds computer vision models for object detection, recognition, classification and tracking, extending state-of-the-art architectures and running large-scale multi-GPU training on sensor data. Optimises models for real-time performance on constrained target hardware and collaborates with research, engineering and product teams to shape perception roadmaps.

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.

Helsing · Berlin, Germany

Builds and benchmarks computer vision systems for scene matching, geo-registration, SLAM, visual odometry and 3D reconstruction, adapting state-of-the-art geometric deep learning to real-world conditions and constrained hardware. Works within a scene understanding and localisation team, collaborating across research, engineering and product to integrate outputs into navigation and decision-making pipelines.

Scale AI · United Kingdom · US$300 pa

Research Advisors apply domain expertise in finance, law or medicine to design and evaluate frontier generative AI systems, building benchmarks and computable frameworks for model evaluation. They partner with product, research and GTM teams, support executive client engagements, and co-author technical reports and papers. The role is a flexible part-time contract within an interdisciplinary expert network.

Maxwell Bond · London · £150,000 – £175,000 pa

Hands-on role building LLM agent and retrieval systems on a small UK core team, reporting to the Head of Engineering. Work spans LangGraph/LangChain workflows, RAG pipelines with Qdrant and GraphRAG on Neo4j, model integration across Anthropic, OpenAI and Bedrock, plus evaluation harnesses and observability. Token cost, latency and auditability are treated as engineering constraints throughout.