Lead Machine Learning Engineer
Faculty · London, England ·
Overview Lead the technical direction and delivery of complex AI initiatives within a regulated services context. Collaborate with cross-functional teams to design scalable ML systems, justify architecture choices, and guide multi-workstream delivery.
Mentor engineers, drive adoption of new technologies, and act as a trusted technical advisor for clients. This role combines deep ML expertise with leadership to build reusable solutions that advance responsible AI at scale.
Pay / Benefits Unlimited Annual Leave Policy Private healthcare and dental Enhanced parental leave Family-Friendly Flexibility & Flexible working Sanctus Coaching Hybrid Working Responsibilities Set technical direction for complex ML projects and align priorities Design, implement, and maintain scalable ML/software systems with architectural justification Define problems, create roadmaps, and oversee multi-workstream delivery in high-risk environments Develop shared resources and libraries; mentor engineers to contribute Lead hiring processes and mentor team members to foster growth Introject new technologies and adapt ways of working to stay ahead Act as technical expert and coach for customers; estimate large workstreams and defend rationale Lead client-facing discussions and ensure successful project outcomes Key requirements Strong Python skills with hands-on experience deploying models using Scikit-learn, TensorFlow, or PyTorch Expert in at least one major Cloud Provider (Azure, GCP, AWS) with experience leading full-stack web apps Hands-on experience with Docker and Kubernetes Proven ability to manage and coach a team of engineers toward client delivery goals Ability to propose novel solutions and take ownership of project outcomes Excellent communicator, capable of guiding both technical teams and non-technical stakeholders excellent communication leadership mentoring Python Scikit-learn TensorFlow