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# Lead Machine Learning Engineer

- **Company:** 17918
- **Location:** Ruislip, UK
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Python (Programming Language), Machine Learning, Tensorflow, Pytorch, Containerization, Scikit Learn, Kubernetes, Machine Learning Operations, Docker
- **Published:** July 27, 2026
- **Apply:** https://www.apply4u.co.uk/jobs/x/42208369/

## About the Role

foster technical growth and collaboration. Advise clients as a technical expert, providing estimates and rationale for high-impact work. What we need from a Lead Machine Learning Engineer: Strong Python skills and experience operationalising models with frameworks like Scikit-learn, TensorFlow, or PyTorch. Cloud and full-stack experience (AWS, Azure, or GCP) with containerisation (Docker) and orchestration (Kubernetes). Recognised technical expert with deep ML knowledge and broad problem-solving ability. Excellent communicator, guiding teams and clients to deliver impactful AI solutions. As a Lead Machine Learning Engineer, whats in it for you? Competitive salary Unlimited holidays Private medical and dental cover TPBN1_UKTJ

## Description

Lead Machine Learning Engineer Location: London Work model : Hybrid 2 days on site Salary: Up to £125,000 + Package Who youll be working with: As a Lead Machine Learning Engineer, youll drive the technical direction of complex AI projects, designing robust architectures and deploying cutting-edge solutions with clients. This hands-on role blends deep technical expertise with leadershipfostering team growth, driving innovation, and delivering high-impact, practical AI outcomes. What youll have the opportunity to do as a Lead Machine Learning Engineer: Set the technical direction for complex ML projects, balancing trade-offs and guiding team priorities. Design, implement, and maintain reliable, scalable ML systems, making sound architectural decisions. Define project problems, develop roadmaps, and oversee delivery across multiple workstreams. Build reusable ML tools and libraries and guide the team in applying them effectively across projects. Lead hiring, mentor team members, and


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