About the role
As a Principal Machine Learning Engineer, you'll serve as the definitive technical authority on ML engineering across the organisation, setting the standard for how we design, build, and scale AI systems. You will own the architectural vision for our most complex and high-stakes programmes, influence engineering strategy at an organisational level, and act as a trusted partner to senior leadership and executive clients.
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.
Requirements
•You are a recognised ML engineering authority, able to go exceptionally deep across multiple domains and provide definitive technical judgement on the hardest problems.
•You have mastery of Python and a proven track record of designing and operationalising production-grade ML systems at scale, across multiple frameworks and paradigms.
•You are an expert across multiple major Cloud Solution Providers and have set the architectural direction for complex, full-stack AI platforms spanning multiple organisations.
•You have deep expertise in containerisation, orchestration, and MLOps at scale, and have established the standards others follow.
•You have a proven track record of developing senior engineering talent, coaching leads and managers, building capability, and shaping high-performance engineering cultures.
•You have a visible external profile, through publications, conference contributions, open-source leadership, or industry influence, that reflects your standing in the field.
•You operate naturally at the executive level, translating complex ML engineering decisions into commercial outcomes and proactively shaping the strategic direction of client engagements.
Conditions
We are open to conversations about part-time hours.
