Artificial Intelligence Jobs

Wayve · London

Lead large-scale data enrichment and curation for the Core Model Safety team, mining hard and rare events and building workflows across pre/mid-training, reward modelling and self-supervised labelling. Design and train out-of-distribution detection mechanisms for robust driverless operation, working at the intersection of model engineering, infrastructure, compute and data.

Faculty · London

Lead the design, build and deployment of production-grade ML systems for national security and AI safety clients, including capability testing of frontier models. Act as a technical advisor to customers, define best practices for deploying ML at scale, and mentor junior engineers. Distinct for its focus on red teaming, evaluation and high-stakes government and frontier lab work.

Wayve · London

Owns the engineering release process for autonomous driving models, defining branching strategies, release cadence, configuration management and quality gates. Reviews model, architecture and code changes against intended outcomes, assesses evaluation results and builds CI/CD tooling and observability to deliver ML systems reliably at scale.

Faculty · London

Set technical direction for complex AI/ML projects, leading delivery of large-scale platforms in high-risk national security environments. Define roadmaps across multiple workstreams, justify architectural decisions to senior stakeholders, and coach engineers while building shared deployment and CI/CD infrastructure. Requires DV eligibility and occasional on-site client work.

Relation Therapeutics · London

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.

MFK Recruitment · Brentford · £70,000 – £95,000 pa

Design and deploy production-grade computer vision systems using deep learning techniques such as CNNs and Vision Transformers, translating research into robust AI solutions for defence and security applications. Work across the full development lifecycle, from model design and training to deployment on cloud and edge platforms. Collaborate with researchers, engineers, and customers in a technically challenging environment focused on real-world autonomy and perception systems.

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.

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.

Adria Solutions · Huddersfield · £55,000 – £70,000 pa

Develops software and applied AI models for machine vision, working across C++, C# and Python to build image-processing algorithms and integrate models into reliable applications. Involves dataset preparation, model evaluation, performance tuning for accuracy and inference speed, automated testing and debugging of vision pipelines. Hybrid or remote, with a path to lead an AI team.

Isomorphic Labs · Lausanne, Switzerland

Architect and secure an AI-first drug discovery platform, reporting to the CISO. You will build AI-specific risk frameworks, protect model artifacts, deploy LLM and agentic guardrails, and lead AI security incident response across distributed training and inference infrastructure.

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.

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.

Salt Search · London · £70,000 – £100,000 pa

Build and scale a cloud-native AI platform for real-time video security, working across Go and Python backend services and React/TypeScript frontends. You'll design APIs and distributed systems handling real-time video and sensor data, collaborating closely with product and ML engineers and owning features from design to production.

Adria Solutions · Huddersfield · £35,000 – £45,000 pa

Supports AWS infrastructure, CI/CD pipelines and automation for software and machine learning workloads, including packaging, versioning and deploying ML models. Works alongside software and AI engineers to keep development, testing and production environments consistent, monitoring pipelines and fixing issues. Suited to an early-career engineer with cloud, scripting and Git foundations and an interest in MLOps.