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Principal Machine Learning Engineer

Faculty· Engineering
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Hybrid (London)Full-timePosted 3mo ago

About the role

Technical leader and authority on ML engineering, shaping architectural standards, driving end-to-end delivery of flagship ML programmes, and partnering with executive clients to align ML strategy with business goals.

Responsibilities

  • Defining and owning the organisation-wide technical vision for ML engineering, establishing architectural standards and engineering practices that scale across teams and clients.
  • Overseeing the end-to-end delivery of flagship, business-critical ML programmes, spanning multiple workstreams, engineering teams, and client organisations.
  • Driving the strategic adoption of new technologies, platforms, and ways of working, influencing how the entire engineering craft evolves.
  • Cultivating senior engineering talent, coaching leads and managers, building capability pipelines, and embedding a culture of technical rigour and excellence.
  • Acting as the principal technical voice in C-suite and executive client engagements, shaping AI strategy and securing long-term strategic partnerships.
  • Leading on the most significant sales and pre-sales opportunities, providing architectural authority that differentiates our proposition and wins high-value engagements.
  • Partnering with Data Science, Commercial, and Infrastructure leadership to align ML engineering strategy with broader business goals and growth ambitions.

Qualifications

  • You are a recognised ML engineering authority, able to go exceptionally deep across multiple domains and provide definitive technical judgement on the hardest problems.
  • Mastery of Python and a proven track record of designing and operationalising production-grade ML systems at scale, across multiple frameworks and paradigms.
  • Expert across multiple major Cloud Solution Providers and have set the architectural direction for complex, full-stack AI platforms spanning multiple organisations.
  • Deep expertise in containerisation, orchestration, and MLOps at scale, and have established the standards others follow.
  • Proven track record of developing senior engineering talent, coaching leads and managers, building capability, and shaping high-performance engineering cultures.
  • Visible external profile through publications, conference contributions, open-source leadership, or industry influence.
  • Ability to translate complex ML engineering decisions into commercial outcomes and proactively shaping the strategic direction of client engagements.

Skills

Required:PythonCloud platformsMLOpsLeadership/coachingArchitectural vision & strategy

Benefits

  • (Not specified in the description)
Last updated Oct 21, 2026. Interested? Apply on the company site.
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