Artificial Intelligence Jobs

Faculty · Remote (UK)

Lead the design, build and deployment of production-grade ML systems for defence clients, covering architecture, scalable infrastructure and MLOps standards. Work cross-functionally with engineers, data scientists and commercial teams, acting as a technical advisor and mentoring junior engineers. Requires on-site work with customers 2-4 days per week and eligibility for UK Security Clearance.

Faculty · Remote (UK)

Lead the technical direction and delivery of complex, high-risk AI projects for defence clients, balancing deep ML engineering with team leadership. You'll design scalable ML systems, set architecture, build shared libraries, mentor engineers, and work on-site with customers 2-4 days a week, with the rest remote or from the London office.

Wayve · London

Builds reusable Python libraries and platform tooling for multimodal data loading, distributed training, inference, checkpointing and observability, supporting ML teams running models across thousands of GPUs. Partners closely with researchers to turn complex workflows into stable, scalable software, leading projects from discovery to delivery. A software and platform engineering role rather than ML modelling.

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

Builds and deploys customer-facing applications that put physics AI models into production, working directly with customers, data scientists and ML engineers. Involves rapid prototyping, RESTful APIs in Python (FastAPI), microservices, and cloud deployment with Kubernetes, Helm, Terraform and AWS/Azure, plus 3-4 weeks of travel per quarter to customer sites.

PhysicsX · Singapore

Builds and applies advanced thermal, chemical and multiphase CAE models in Abaqus, ANSYS or COMSOL, coupling heat transfer with fluid, diffusion and electrostatic phenomena. Works directly with customers, often on-site, instrumenting physical processes to generate validation data and integrating models into AI tools. Combines shop-floor manufacturing experience with Python/Java automation and parametric CAD.

Wayve · London

Builds ground-truth datasets and computer vision classifiers that describe complex driving scenes across Wayve's data corpus, drawing on the World Foundation Model to surface rare scenarios and performance gaps. Day to day spans defining annotation tasks and quality criteria, curating datasets, training and evaluating models in PyTorch, and integrating classifiers into enrichment infrastructure for corpus-wide inference.

Rise Technical Recruitment · London · £80,000 – £120,000 pa

Builds, evaluates and optimises LLM, agentic AI and computer vision systems for financial crime compliance, including fine-tuning foundation models and training custom models. Develops benchmarks, back-testing and evaluation pipelines, and creates human-feedback improvement loops, working closely with engineering and product teams.

Helsing · London

Architect and scale the deep learning frameworks and distributed training infrastructure behind defence AI systems, extending PyTorch-based tooling and optimising GPU throughput. The role spans data strategy, storage and orchestration, working cross-functionally to maximise training efficiency and developer velocity.

M4 Partners · Stratford-upon-Avon

Hands-on product development role building and improving machine learning and AI capabilities for an in-house AI platform, taking ideas from business requirements through experimentation, evaluation and deployment. Focus on producing reliable structured JSON outputs, AI workflows for extraction, classification, retrieval and summarisation, plus evaluation datasets, monitoring and API integration with developers.

University of Glasgow · Glasgow · £50,253 – £58,225 pa

Develops physics-informed machine learning and uncertainty quantification methods to improve subsurface characterisation for offshore wind and net-zero infrastructure. Joins an interdisciplinary team of engineers, data scientists and geophysicists within a UKRI-funded Fellowship, with scope to shape an ambitious research programme.

NVIDIA · Cambridge

Develops algorithms and optimizations for NVIDIA's LPX inference and compiler stack, building high-performance runtime and compiler components for end-to-end inference. Involves mapping large-scale neural network workloads onto future hardware, working with LLVM/MLIR, and collaborating with hardware architects on codesign. Hybrid role based in Cambridge.

NVIDIA · United Kingdom

Develops algorithms and optimizations for NVIDIA's LPX inference and compiler stack, building high-performance runtime and compiler components and mapping large-scale inference workloads onto future hardware. Works at the intersection of compilers, systems and deep learning, using LLVM/MLIR and frameworks like PyTorch and TensorFlow, and collaborates with hardware architects on codesign.

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

Blends research and engineering to advance reinforcement learning for large language models, building agentic capabilities like computer use and autonomous code generation. Involves architecting distributed RL training infrastructure across GPU clusters, designing novel training environments and evaluations, and profiling and optimizing the stack. Works closely with alignment, red team, and production training groups.

Anthropic · London · £370,000 – £630,000 pa

Builds and improves the core RL training infrastructure researchers rely on, profiling, debugging and rearchitecting bottlenecks across the stack. Partners with researchers and adjacent engineering teams to ship tooling that speeds up training runs, owning reliability and performance end-to-end.

Latent Labs · London

Architect novel generative models to design functional proteins, working in an interdisciplinary team of ML researchers, protein engineers and biologists. The role spans data curation, evaluation metrics, rapid prototyping, cloud training and inference, and planning wet lab testing campaigns, with about 10% of time for self-development.