Artificial Intelligence Jobs

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.

CrowdStrike · Germany

Builds and operates large-scale data processing pipelines, storage systems and presentation layers for the Intelligence team, owning systems from design and prototyping through production deployment and long-term maintenance. Works fully remotely with analysts as internal customers, choosing your own tech stack across Go, Python, SQL/NoSQL and cloud.

Faculty · London

Lead the development of novel safety evaluations quantifying AI risks in high-impact domains such as CBRN and Cyber, executing original technical research from concept to publication. Shape the R&D agenda, contribute to client delivery and red-teaming for frontier labs, and engage externally with the global research community. The role sits in a central R&D team focused on fundamental and applied technical AI safety research.

University of Oxford · Oxford · £21,805 pa

Investigates how the rapid growth of AI can be supported by more sustainable, circular hardware and infrastructure, linking computational performance to the physical materials and equipment required. Develops scenarios for UK AI and data centre growth, mapping hardware requirements to critical raw materials and modelling how lifetime extension, reuse, repair and remanufacture could cut environmental impacts. Based in the Circular Economy and Sustainability Lab, contributing to the Circular Electricals and Electronics Project.

Opus Recruitment Solutions · United Kingdom · £80,000 – £90,000 pa

Designs enterprise-scale AI, data and automation solutions, architecting generative and agentic AI, RAG, vector database and multi-agent systems across OpenAI, Azure OpenAI, Anthropic and Google Gemini. Runs customer discovery and solution-design workshops, creates reference architectures and roadmaps, and supports technical pre-sales, governance and Responsible AI. Remote-first with client site visits.

Databricks · London

Lead and scale the UK Forward Deployed AI Engineering team, delivering professional services engagements that help EMEA customers productionise GenAI and ML applications. The role combines people leadership, executive customer relationships, and cross-functional work with Product, Research and Sales to shape delivery models and the product roadmap.

Wayve · London

Owns validation strategy for ADAS and L2 autonomy functions, translating product, safety and regulatory requirements into test scenarios, metrics, coverage and acceptance criteria. Works hands-on with Python evaluation pipelines, simulation and SQL-based data analysis, spanning simulated and physical test environments. Open at senior IC or manager level, with close collaboration across Product, Safety and Release stakeholders.

University of East Anglia · Norwich · £21,805 pa

A PhD studentship developing multispectral and hyperspectral imaging combined with machine learning to detect and classify marine litter from aerial and drone-based platforms. The researcher will characterise litter material reflectance in the lab, curate imaging datasets, and build models robust to changing illumination and sensor differences, based in the Colour & Imaging Laboratory and working with CEFAS scientists.

University of Surrey · Guildford · £21,805 pa

Develops next-generation federated machine unlearning algorithms that deliver verifiable, robust erasure without harming model performance or participant privacy. Research spans certified unlearning with formal guarantees, robustness to adversarial relearning, federated-specific benchmarks, and scalable unlearning for foundation models, supervised by Dr Pedro Porto Buarque de Gusmao and Dr Frank Guerin.

Harnham - Data and Analytics Recruitment · London · £70,000 – £80,000 pa

Build, scale and maintain backend services including APIs, workflow engines and data services, integrating Java/Spring components with Python-based AI services. Work across AWS cloud infrastructure, CI/CD pipelines, observability and security best practices in a collaborative, fast-paced product team.

Harnham - Data and Analytics Recruitment · London · £75,000 – £85,000 pa

Owns the infrastructure, deployment and operational excellence of production machine learning systems within a growing AI and data organisation serving the public sector. Builds ML orchestration pipelines with Dagster, Airflow or Prefect, runs Kubernetes and Terraform/Bicep infrastructure, and maintains CI/CD and observability for models and LLM-powered solutions, working closely with data scientists and client-facing teams.

Scale AI · United Kingdom

Finance experts design and evaluate complex financial scenarios—valuation, forecasting, risk assessment and equity research—to test and improve generative AI models, giving detailed feedback on outputs for market relevance and compliance. Fellows may co-author research publications with Scale's team and work flexible 10–40 hour weeks within an interdisciplinary network.

Scale AI · London

Leads a forward-deployed engineering team acting as the technical bridge between AI capabilities and strategic enterprise customers. Involves designing custom integrations, ETL pipelines and production AI agents, plus prompt engineering, RAG systems and evaluation frameworks, deployed within customer security and compliance boundaries.

Signal AI · London

Full-stack engineer owning revenue-critical products end to end, from problem discovery with research, design and product through to production. Day to day involves building UIs and data visualisations, large-scale distributed services, AWS infrastructure and observability, with heavy pair programming and AI-assisted development using tools like Claude Code.

Isomorphic Labs · London

Research engineers translate frontier research concepts into practical implementations, building and optimising state-of-the-art AI models such as Transformers, GNNs and diffusion models, plus the codebases, data pipelines and infrastructure for training and evaluation. They design and run experiments, analyse model performance, and advise on bringing models to production, working closely with research scientists in a cross-disciplinary team.