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.

Wayve · London

Owns the architecture, strategy and integrity of safety cases for robotaxi and OEM ADAS products, defining top-level claims, argumentation structures and evidence traceability. Sits independently from Engineering and Product, providing expert challenge and oversight across AI/ML, systems, validation and operational safety. Requires deep safety-case and systems engineering expertise in safety-critical domains.

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.

NVIDIA · Reading

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. Develop and demonstrate GenAI and accelerated computing solutions, optimise GPU training and inference pipelines, and engage developers, researchers and senior technical leaders.

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.

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.

Local Pensions Partnership Administration · Preston · £90,000 – £100,000 pa

Lead AI strategy, governance and delivery across a major UK pension administration organisation, working with the CTO and executive team to identify and scale AI opportunities. Establish responsible AI frameworks, build and manage a specialist AI team, and oversee adoption of tools such as Microsoft Copilot, Civica UPM and UiPath. The role combines strategic leadership, risk assurance and supplier engagement to drive measurable service improvements.

Adecco · London · £700 – £800 pd

Drives enterprise-wide AI adoption within an EMEA Data Management Office, bridging business needs and AI capabilities. Develops use cases, playbooks and prompt libraries, runs training and champion networks, and tracks adoption, value and ROI. Hybrid role in London, three days per week on site.

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.