Artificial Intelligence Jobs

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.

CrowdStrike · Germany

Security researcher on CrowdStrike Intelligence's Advanced Research Team, developing automated tooling to collect, process and analyse data at scale, including vendor patch analysis and exploit identification in large file collections. The role involves vulnerability research, reverse engineering, and reproducing 0-day and n-day exploits, with results published on the blog or at conferences. Work is remote and collaborative, spanning Windows and Linux internals with Python tooling.

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.

Wayve · London

Owns the autonomy performance measurement framework for a public-scale robotaxi deployment, defining metrics, dashboards and release gates for an end-to-end learned driving system with no existing playbook. Runs the performance improvement loop across model, robot software, backend and evaluation tooling, leading cross-functional execution without direct reporting authority while staying hands-on in Python, C++ and SQL.

NVIDIA · France

Serve as the first line of technical expertise between NVIDIA, hyperscaler partners and end-customers, with a primary focus on the Google Cloud (GCP) partnership. Day to day involves proof-of-concept demonstrations, optimising GPU-accelerated training and inference pipelines, and engaging developers, researchers and technical executives to evangelise accelerated computing and Generative AI.

NVIDIA · Cambridge

Serve as the primary technical contact for academic and research partners, driving adoption of NVIDIA's accelerated computing and AI stack. Work directly with labs and faculty on large language model workloads, integrating frameworks and libraries into research projects. Deliver hands-on training, workshops and lectures, and track emerging research trends to shape prototype solutions.