Artificial Intelligence Jobs

• Romania
• Remote
• Senior

Join the Advanced Research Team to perform vulnerability research across a wide range of targets, including analyzing vendor patches, developing proof-of-concept exploits, and confirming exploitation of 0-day and n-day vulnerabilities. The role also involves building automated solutions for collecting and processing data at scale, reverse engineering, and publishing research on the CrowdStrike blog or at conferences.

CrowdStrike · Windows · Linux +5

• Germany
• Remote
• Senior

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 · GenAI · LLM +5

• London
• Hybrid · 3 days in office
• Permanent

Partner directly with engineering organizations to design, build, and deploy AI-powered software development workflows using Codex, from use-case selection through prototyping, evaluation, and production rollout. Combines hands-on coding in Python with customer leadership, building evaluation harnesses, integrations, and reusable architectures while feeding deployment insights back to Product and Research teams.

Codex · OpenAI · OpenAI Cookbook

• London
• Senior

Own the AI behaviour of production systems for public sector clients, covering agents, model integration, evaluation design and the backend services they run on. Lead delivery for a workstream, act as the technical client contact on live-data performance, and mentor other engineers.

• London
• Senior · manages people

Lead and grow Scale AI's enterprise product design team, setting the direction for design across applications used by enterprise and government customers making high-stakes decisions. Own hiring, craft standards, and design execution from problem scoping to delivery, while shaping interaction patterns for human-in-the-loop and agentic AI systems.

AI Agents

• London
• Hybrid · 3 days in office
• Senior · manages people

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.

JAX · PyTorch · TensorFlow +3

• London
• Hybrid · 3 days in office
• Mid-level · manages people

Builds greenfield machine learning models and algorithms for drug discovery, designing new architectures, running experiments, and scaling training and inference frameworks. Works in an interdisciplinary team of ML scientists and domain experts, with opportunities to lead projects and mentor others depending on experience.

JAX · PyTorch · TensorFlow +3

• London
• Hybrid
• Senior
• Permanent

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.

Language Models · Generative AI

• Munich - Berlin - London - Paris

Build and scale a GPU-based simulator that trains reinforcement-learning agents for air autonomy, modelling flight dynamics and sensing across thousands of parallel environments. Work spans sim-to-real transfer, domain randomisation and RL training tooling, at the intersection of AI, GPU computing and physics-based simulation, with room to grow into leadership.

CUDA · Taichi · NVIDIA Warp +3

• Barcelona, Spain
• Hybrid
• Entry level
• Internship

PhD research internship tackling open problems in spatial perception and localisation within the Spatial Intelligence Team. You survey and prototype state-of-the-art methods for scene matching, SLAM/VIO and 3D reconstruction, benchmarking ideas against real-world data and compute constraints, and report findings to a Europe-distributed team.

PyTorch · NeRF · Gaussian Splatting

• London
• Hybrid
• £260,000 – £370,000 pa

Designs and runs machine learning experiments to understand and steer the behaviour of powerful AI systems, with a focus on AI control and alignment stress-testing. Works closely with interpretability, fine-tuning and red-team researchers, building tooling, multi-agent RL experiments and jailbreak evaluations, and contributing to papers and blog posts.

Python · Kubernetes · LLM +1

• Cambridge
• Hybrid
• Permanent

Join a small, dynamic R&D team prototyping and implementing new approaches to AI problems, evaluating output quality, efficiency and feasibility against other techniques in a data-driven way. Work spans data science on large datasets, modelling and evaluation, using Python ML frameworks such as PyTorch, TensorFlow and Scikit-Learn. Open to graduates as well as senior candidates with published work in NLP, Computer Vision or Deep Learning.

Python · PyTorch · TensorFlow +1

• Oxford
• On-site
• £49,119 – £58,265 pa
• Senior
• Contract

Develops and validates machine learning models for disease forecasting and simulation models for scenario exploration, using large-scale epidemiological, genomic and behavioural data. Builds decision-support tools and reproducible pipelines, integrating them into public health workflows with partners in Nigeria and the DRC through co-design workshops and training.

• London
• On-site
• Senior
• Permanent

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.

PyTorch · CUDA · Triton +1

• Oxford
• £21,805 pa
• Entry level
• Contract

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.

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