Artificial Intelligence Jobs

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.

CrowdStrike · Israel

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 analyzing vendor patches, identifying exploits in large file collections, reverse engineering, and building automated data collection and analysis tooling, with published research on the blog or at conferences.

Wayve · London

Lead functional safety activities for an end-to-end autonomous driving system, building Item Definitions, running HARA/FMEA/FTA analyses, and shaping safety concepts and architectures across vehicle platforms and third-party systems. Define verification and validation, including vehicle-level testing, and construct structured safety cases with claims, arguments and evidence to support certification.

NVIDIA · Cambridge

Lead security research, architecture and implementation for next-generation networking products, taking a hands-on role defining hardware and software security solutions. Work across teams and with external partners on IO interfaces, boot architecture, RISC-V, root-of-trust and secure platforms, guiding open-source implementation and customer threat resolution.

NVIDIA · Bristol

Lead security research, architecture and implementation for next-generation NVIDIA Networking products, taking a hands-on role defining hardware and software security solutions. Work across hardware, software, research and product teams, plus external partners, on IO interfaces, boot architecture, RISC-V, root-of-trust and secure platforms.

Faculty · London

Lead high-impact AI safety projects for Frontier Labs, inventing novel evaluation frameworks and designing robust software architectures. Mentor technical team members while partnering with commercial teams to scope work and translate complex problems into rigorous frameworks. Requires Python, NumPy, Pandas and ideally evaluation tooling like Inspect AI.

Scale AI · United Kingdom

Fellows design domain-specific problems and datasets to evaluate generative AI models, then provide expert insight to improve their accuracy and reasoning. Work is project-based with partnered AI labs, including co-authoring technical reports and research papers with Scale's research team. Fully remote, flexible 10-40 hour weeks within an interdisciplinary network.

IQVIA · Reading

Supports a global pharmaceutical client by applying statistical methods to biological, biomedical and omics datasets, building reproducible analytical workflows in R and/or Python. The role sits at the intersection of statistics, data science and AI, developing AI-enabled tools, agents and automation that speed up discovery and translational research decisions alongside scientists and engineers.

Isomorphic Labs · London

Lead and contribute to core machine learning research applying large language models to drug discovery, developing and refining LLM-driven approaches across biology and chemistry problems. Work spans post-training, reasoning, test-time scaling, tool-use, alignment, agents, reinforcement learning and fine-tuning, with model training and inference engineering at scale. Interdisciplinary collaboration with research scientists and engineers, plus technical mentorship and project leadership depending on experience.

Multiverse · London

Deliver technical AI content across the AI for Business Value and AI-Powered Productivity programmes, facilitating workshops and drop-in sessions for apprentices. Moderate assignments, provide feedback, and coordinate with coaches and operations to track learner progress. Requires applying AI in business contexts and explaining complex concepts to varied audiences.

Wayve · London

Owns reliability of large-scale GPU, Kubernetes and distributed AI training infrastructure, turning recurring operational problems into durable engineering solutions. Improves observability, automation, deployment safety, capacity planning and incident learning, and builds GitOps delivery with Argo CD or Flux. Works across AI Platform, Compute & Data Platform and Cloud Infrastructure teams.

eFinancialCareers · London

Lead technical architecture and hands-on delivery of production-grade agentic AI systems for critical banking workflows within an embedded business engineering team. Build end-to-end workflows using Python, ADK, LangGraph and the Arc platform, integrating agents with core banking systems, enterprise APIs and custom MCP servers, while mentoring engineers and shaping reusable enterprise AI capabilities.

Anthropic · London · £255,000 – £325,000 pa

Product engineer building internal tools and platforms, working across backend, frontend and infrastructure with Python, TypeScript and React. The role sits at the intersection of engineering, product and design, requiring direct user consultation, spotting patterns across requests and turning them into reusable primitives and abstractions rather than one-off features.

eFinancialCareers · London

Lead a small, high-performing team of 6-7 engineers owning core ML infrastructure, including distributed model training, LLM hosting and fine-tuning, and scalable deployment systems. The role combines hands-on technical direction with people leadership, integrating advanced ML capabilities into production-grade, high-stakes systems. Suited to experienced engineering managers, not first-time managers.

Anthropic · London · £325,000 – £485,000 pa

This role involves owning and scaling Kubernetes control plane components to support Anthropic's large-scale AI training infrastructure. You'll extend the scheduler for topology-aware and gang scheduling of ML workloads, operate core cluster services like service discovery, and ensure high availability across multi-cloud accelerator fleets. The work is deeply technical, focusing on reliability and performance at extreme scale in collaboration with research and inference teams.