2 months ago
London, United KingdomStaff+
Responsibilities
- Define and own the organisation-wide technical vision, architectural standards, and engineering practices for ML engineering.
- Oversee end-to-end delivery of complex, business-critical ML programmes across multiple workstreams, teams, and client organisations.
- Drive strategic adoption of technologies, platforms, and engineering practices across the organisation.
- Coach senior engineers, leads, and managers while building capability pipelines and a high-performance technical culture.
- Represent the technical function in executive client engagements and shape AI strategy and strategic partnerships.
- Lead technical input for significant sales and pre-sales opportunities.
- Partner with Data Science, Commercial, and Infrastructure leadership to align ML engineering strategy with business goals.
Requirements
- Recognised authority in ML engineering with deep expertise across multiple domains and strong technical judgment.
- Mastery of Python and a proven record designing and operationalising production-grade ML systems at scale.
- Expertise across multiple major cloud solution providers and experience setting architectural direction for complex, full-stack AI platforms.
- Deep expertise in containerisation, orchestration, and MLOps at scale.
- Proven experience developing senior engineering talent, coaching leads and managers, and shaping high-performance engineering cultures.
- Visible external profile through publications, conference contributions, open-source leadership, or industry influence.
- Ability to operate at executive level and translate complex ML engineering decisions into commercial outcomes.
Benefits
- Part-time hours are open for discussion.
- The interview process includes a talent screen, role introduction, pair programming interview, system design interview, and commercial and leadership interview.
- Candidates may use AI for research and interview preparation, but not to generate answers during live interviews; interview note-taking uses Metaview and candidates may opt out.
- Faculty encourages applications from people of all backgrounds and reviews every application by a human.
Tech Stack
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