Artificial Intelligence Jobs

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.

Isomorphic Labs · London

Lead the hardening and scaling of an inference platform serving fleets of cutting-edge ML models for scientific applications. Set strategy and roadmaps, architect next-generation services to solve scaling limits, and partner with research, product and operations teams to align infrastructure with biotech R&D cycles.

Relation Therapeutics · London

Process and QC paired single-cell RNA-seq and scATAC-seq at scale, building Nextflow pipelines for custom combinatorial indexing chemistries and integrating multimodal datasets for GPU-accelerated model training. Partner with wet lab scientists and ML modellers to design evaluation frameworks that test whether models capture meaningful biology.

NVIDIA · Zürich, Switzerland

Research and develop techniques to GPU-accelerate leading high performance computing applications across scientific computing, computational engineering and data science. The intern performs in-depth analysis and optimisation for current and next-generation GPU architectures, working directly with application developers and collaborating with architecture, research, libraries, tools and system software teams.

Darktrace · Cambridge

Contributes to security research projects spanning rapid prototyping and open-ended initiatives, with a focus on generative AI security and attacker tradecraft. Investigates threats such as prompt injection, poisoning and extraction attacks, and provides feedback to product, development and machine learning teams. Hybrid role requiring two days a week in the London or Cambridge office.

Darktrace · London

Contributes to projects spanning rapid prototyping and open-ended research into generative AI security, investigating attacker tradecraft such as prompt injection, poisoning and extraction attacks. Acts as a domain expert feeding insights back to product, development and machine learning teams, with coverage in network, endpoint, cloud or Kubernetes.

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.

Helsing · 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.

Anthropic · London · £195,000 – £245,000 pa

Conducts empirical research on AI's economic effects, building and extending the Anthropic Economic Index with regionally relevant insights. Develops new methodologies using econometrics, machine learning and structural estimation, and engages governments, academia and industry as a primary research partner. Combines novel datasets with causal inference to inform policy and internal product decisions.

Amazon · London

Customer-facing cloud architect role in AWS's UK Solutions Architecture team, focused on the Travel and Hospitality industry. You lead architecture reviews, whiteboarding sessions, demos and technical workshops, manage the technical relationship with customers, and create reference architectures and best practices across AI/ML, serverless, containers, analytics and security.

Anthropic · London · £260,000 – £630,000 pa

Join the Pretraining team to develop next-generation large language models, working across model architecture, algorithms, data processing and optimizer development. You'll lead small research projects, design and analyse experiments, and scale distributed training infrastructure to thousands of GPUs, balancing research goals with practical engineering.

PhysicsX · New York, United States · US$150,000 – US$250,000 pa

Builds and deploys customer-facing applications on top of physics AI models, working directly with clients, data scientists and ML engineers. Involves full-stack work: FastAPI REST APIs and Python microservices, plus cloud deployment with Helm, Kubernetes, Terraform and AWS/Azure. Expect on-site travel to customer sites for 3-4 weeks per quarter.

University of West London · London · £18,000 pa

Develops an AI-enabled decision-support framework combining building-performance simulation, machine learning, GIS and remote sensing to optimise green roofs and façades for energy, carbon and thermal performance. Primarily computational, with no routine lab or fieldwork, and scope refined with the successful candidate.

PhysicsX · London

Builds the simulation side of Large Physics Models, generating multi-fidelity CFD data to train large-scale ML models. Develops solvers and numerical methods in differentiable or GPU-native frameworks such as JAX or NVIDIA Warp, using commercial and open-source CFD tools for reference data. Works in a research team alongside ML researchers, shaping data generation strategy and fidelity tradeoffs.

Databricks · London

Customer-facing pre-sales architect driving adoption of Databricks' AI product line across a local EMEA territory, paired with an Account Executive to design and execute engagement strategies. Leads design and implementation of production agentic AI use cases using Agent Framework, AgentBricks, MLflow evaluation and tracing, while acting as tier-3 escalation for complex field challenges.