Machine Learning Jobs

Wayve · London

Lead large-scale data enrichment and curation for the Core Model Safety team, collaborating across pre/mid-training, reward modelling and self-supervised labelling. Build workflows for hard and rare event mining, design out-of-distribution detection for driverless operation, and improve ML operations efficiency across model engineering, infrastructure and compute.

Faculty · London

Lead the design, build and deployment of production-grade machine learning systems for clients across life sciences, government and finance. Work spans architectural scoping, scalable cloud and Kubernetes infrastructure, and acting as a trusted technical advisor to customers while mentoring junior engineers.

Faculty · Remote (UK)

Lead the design, build and deployment of production-grade machine learning systems for defence-sector clients, covering architecture, scalable infrastructure and MLOps standards. Work cross-functionally with engineers, data scientists and commercial teams while acting as a trusted technical advisor to customers. Requires eligibility for UK Security Clearance and 2-4 days per week on client sites.

Cambridge Consultants · United Kingdom

Architect algorithmic approaches on complex defence and security projects, acting as technical lead and authority across the department. Hands-on work spans machine learning, applied statistics, sensor processing, signal processing and numerical optimisation, alongside client-facing proposal development and mentoring engineers.

Cambridge Consultants · United Kingdom

Senior technical role architecting agentic AI systems for defence and security clients, acting as technical lead on complex projects and setting departmental technical direction. Involves hands-on engineering in Python, client-facing proposal work, mentoring engineers and conducting technical interviews. Requires SC security clearance and UK residency.

Harnham - Data and Analytics Recruitment · France · €130,000 – €150,000 pa

Define the technical direction of large-scale production ML systems while remaining hands-on across the full model lifecycle, leading end-to-end initiatives in recommendation systems, audience targeting, bidding optimisation and customer lifecycle modelling. Work directly alongside the CTO in a high-scale real-time AdTech environment, combining technical strategy, platform engineering and applied ML as an individual contributor leader rather than a people manager.

Anthropic · London · £255,000 – £325,000 pa

Founding leader for Anthropic's Forward Deployed Engineering practice, hiring and developing a team that embeds with strategic enterprise customers to ship production AI applications. Player-coach role balancing technical review, architecture and debugging with people management, playbook creation and cross-functional work with Sales, Product and Engineering. Requires travel to customer sites 25-50%.

Cohere · London

Optimises large language model training performance, focusing on throughput and accelerator utilisation. Writes low-level CUDA and Triton kernels, works on distributed training strategies, and builds profiling tools within the Pre-Training team. Combines software engineering, ML and kernel design to remove performance bottlenecks.

Cohere · London

Designs and writes high-performance, scalable software for training frontier models, improving the training setup from an infrastructure and codebase performance standpoint. Builds tooling to speed up training cycles and works on supercompute and data infrastructure, bridging research and production. Works with distributed training stacks like Kubernetes, Slurm and Ray, with one of the highest compute-to-engineer ratios in the world.

PhysicsX · New York, United States · US$90,000 – US$130,000 pa

Customer-facing role owning the full account journey for industrial clients, from onboarding and change management to executive reviews and contract preparation. Works alongside simulation, software, ML engineers and data scientists to translate engineering challenges into AI solutions, while building internal tooling to scale account operations.

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

Customer-facing role owning the full customer journey, from onboarding and change management to roadmap planning and contract preparation. Works alongside simulation, software, ML engineers and data scientists to translate industrial engineering challenges into product opportunities, tracking engagement and measuring value. Hybrid role based in Manhattan with remote flexibility.

Adecco · London · £600 – £750 pd

Develops and deploys machine learning models and data pipelines that shape decision-making, customer service and business performance. Works closely with ML and software engineers on integration and coding standards, and communicates findings to technical and non-technical stakeholders. Retail context with scope for personalisation, recommendation and experimentation work.

Wayve · London

Owns the end-to-end release cycle for AI driving models, coordinating ML engineering, evaluation, data science, platform, testing and product teams. Defines release gates and promotion criteria from training through validation to fleet deployment, drives regression investigations and rollback decisions, and builds tooling and KPIs to remove bottlenecks in a non-deterministic ML environment.

AI Security Institute · London · £65,000 – £145,000 pa

Engineers at all levels build and scale the shared tooling and infrastructure behind the institute's AI safety research, from Inspect plugins and large-scale evaluation systems to model hosting and secure proxy infrastructure. Work spans open-source collaboration, supporting research teams with custom setups, and hardening infrastructure for frontier model evaluations.

Leo Technology · London · £60,000 – £70,000 pa

Technical Business Analyst role sitting between business and software engineering, translating complex requirements, mapping system integrations and data flows, and driving process and platform improvements. Works across regulatory change, system enhancements and new platform capabilities, with scope to explore AI, ML and automation, while mentoring less experienced BAs.