Artificial Intelligence Jobs

• London
• Hybrid
• Mid-level
• Permanent

Builds and deploys production-grade machine learning systems for national security and AI safety clients, including LLM applications, multi-agent tooling and evaluation of frontier models. Involves technical scoping, architectural decisions, and advising stakeholders, with reusable infrastructure work alongside engineers and data scientists.

AWS · Azure · GCP +5

• New York, United States
• Hybrid
• Lead

Lead the ML approach to manufacturing and MRO data, from modelling through deployment in customer production environments across cloud, on-prem and edge. Build production ML on sparse, drifting sensor and process data, fusing physics simulation with shop-floor measurement, and set validation and uncertainty-quantification standards. Mentor engineers and data scientists while travelling to customer sites roughly 3-4 weeks per quarter.

Python · PyTorch · Pandas +3

• New York, United States
• Hybrid
• US$200,000 – US$250,000 pa
• Senior

Owns deployment of ML models and engineering surrogates (deep learning on CAE/CFD/FEA data, time-series forecasting, anomaly detection, optimisation) into customer production environments, using Python, PyTorch, Pandas, fastAPI, Scipy and Kubeflow across cloud and on-prem. Leads scoping and architecture for data/ML systems, mentors engineers, and travels to customer sites roughly 3-4 weeks per quarter.

Python · PyTorch · Pandas +3

• London
• Hybrid
• Lead
• Permanent

Lead the technical strategy, architecture and deployment of secure AI systems across high-stakes domains, bridging research and production impact. The role involves capability testing for Frontier AI models, multi-agent systems, scalable cloud infrastructure and safety-first frameworks, while advising senior clients and mentoring engineering talent.

AWS · Azure · GCP +4

• London
• Hybrid
• Senior
• Permanent

Train, debug and improve computer vision and 3D perception models for driver assistance, working across the full ML lifecycle from data and training to evaluation and iteration. The role spans latency-constrained on-car perception and large-scale offline work with lidar, maps and 3D reconstruction to build auto-labelling data flywheels.

LiDAR

• London
• Hybrid
• Senior
• Permanent

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.

PyTorch · CUDA

• London
• Hybrid · 2–3 days in office
• Senior

Join the Modelling Team to train large self-supervised and transformer-based speech models, deploying them into production with strong software engineering and model-serving practices. Work on complex R&D projects, optimise inference, and mentor engineers in a hybrid London setup.

GQA · KV-caching · Flash Attention +2

• London
• Hybrid
• £80,000 – £110,000 pa
• Senior

Design, build and deploy production-grade machine learning and generative AI solutions across the full ML lifecycle, from experimentation to deployment, monitoring and optimisation. The role has a strong MLOps and performance focus, improving Python workloads, infrastructure efficiency and model performance while building APIs and working closely with engineering and AI teams.

• Oxford
• Hybrid
• £81,322 – £112,488 pa
• Lead · manages people
• Permanent

Dual role combining line management of a growing ML engineering team with hands-on technical delivery across concurrent projects. You'll shape ML engineering practice, lead multidisciplinary teams, oversee solution design and quality assurance, and support use case discovery and pre-sales alongside commercial teams.

• Dublin, Ireland
• Hybrid · 2 days in office
• Lead

Lead the architecture, deployment and operation of a large-scale AI/ML platform spanning conventional ML and agentic AI, owning the roadmap and engineering standards. Hands-on role covering MLOps/LLMOps, CI/CD, IaC, Azure infrastructure and multi-agent orchestration frameworks, while mentoring engineers and acting as senior escalation point.

Azure · AWS · Terraform +4

• Kraków, Poland
• Hybrid · 2 days in office
• Senior
• Permanent

Senior ML engineer role in a cross-craft data science team building prediction, ranking and personalisation systems for an e-commerce platform. Owns the full ML lifecycle on production systems, from experimentation and training through serving, monitoring and MLOps, while coaching others and shaping reusable platform building blocks.

GCP · Vertex AI · BigQuery +6

• London
• On-site
• Entry level
• Permanent

Builds and maintains scalable training and inference pipelines for biological foundation models such as Transformers and SSMs, optimising latency and throughput. Works with researchers and product engineers to turn notebooks into production systems, owning ML infrastructure like data loading, distributed compute and experiment tracking while prototyping post-training methods.

• London
• On-site
• £150,000 – £200,000 pa
• Mid-level
• Permanent

Develops and fine-tunes robot manipulation policies using behaviour cloning and reinforcement learning, then trains, evaluates and deploys models onto real humanoid hardware. Works within a specialist Manipulation team alongside simulation, teleoperation and controls engineers to improve sim-to-real transfer and training data quality. Distinct for being hands-on with physical robots rather than purely simulation or research.

PyTorch · JAX · OpenVLA +1

• 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

• Brentford
• Hybrid
• £70,000 – £95,000 pa
• Senior
• Permanent

Hands-on role designing and deploying production computer vision systems using CNNs and Vision Transformers, from model architecture and training pipelines to optimisation for cloud and edge. Involves translating recent AI research into reliable products for defence and security, collaborating with engineers, researchers and customers.

PyTorch · TensorFlow · CUDA +7