Faculty
Principal Machine Learning Engineer
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Why Faculty?
We established Faculty in 2014 because we thought that AI would be the most important technology of our time. Since then, we’ve worked with over 350 global customers to transform their performance through human-centric AI. You can read about our real-world impact here.
We don’t chase hype cycles. We innovate, build, and deploy responsible AI that moves the needle—and we know a thing or two about doing it well. We bring an unparalleled depth of technical, product, and delivery expertise to our clients who span government, finance, retail, energy, life sciences, and defence.
Our business, and reputation, is growing fast, and we’re always on the lookout for individuals who share our intellectual curiosity and desire to build a positive legacy through technology.
AI is an epoch-defining technology. Join a company where you’ll be empowered to envision its most powerful applications and to make them happen.
About the Team
Our Retail and Consumer experts are dedicated to helping clients in an industry being transformed by new technologies and evolving consumer expectations. Leveraging over a decade of experience in Applied AI, we combine exceptional technical and delivery expertise to empower businesses to adapt and thrive. #LI-PRIO
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. This role goes beyond leading projects—you are a force multiplier who shapes the engineering culture, elevates the capability of those around you, and ensures our technical foundations are built to last.
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Responsibilities
- Defining and owning the organisation-wide technical vision for machine learning engineering, establishing architectural 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—helping to influence 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 the 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 judgment on the hardest problems.
- A mastery of Python with a proven track record of designing and operationalising production-grade ML systems at scale, across multiple frameworks and paradigms.
- An expert across multiple Cloud Solution Providers, having set the architectural direction for complex, full-stack AI platforms spanning multiple organisations.
- With deep expertise in containerisation, orchestration, and MLOps at scale, establishing standards that others follow.
- With a proven track record of developing senior engineering talent—coaching leads and managers, building capability, and shaping high-performance engineering cultures.
- With a visible external profile—through publications, conference contributions, open-source leadership, or industry influence, reflecting your standing in the field.
- Operational at executive level, translating complex ML engineering decisions into commercial outcomes and proactively shaping the strategic direction of client engagements.
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Our Interview Process
- Talent Team Screen (30 minutes)
- Introduction to the role (45 minutes)
- Pair Programming Interview (90 minutes)
- System Design Interview (90 minutes)
- Commercial & Leadership Interview (60 minutes)
Our Recruitment Ethos
We aim to grow the best team—not the most similar one. We believe that diversity of individuals fosters diversity of thought, strengthening our principle of seeking truth. Our experience shows that diverse teams deliver better work, more relevant to the world we live in. We’re united by a deep intellectual curiosity and a desire to use our abilities for measurable positive impact. We strongly encourage applications from people of all backgrounds, ethnicities, genders, religions, and sexual orientations.
Benefits
We offer a range of standout benefits to enable success and balance in your role:
- Unlimited Annual Leave Policy
- Private health care and dental
- Enhanced parental leave
- Family-Friendly Flexibility & Flexible Working
- Sanctus Coaching
- Hybrid Working
If you don’t feel you meet all the requirements but are excited by the role and know you bring key strengths, please don't hesitate to apply. You might be right for this role or another role we have live. We are also open to conversations about part-time hours.
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