Senior Machine Learning Engineer

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 https://faculty.ai/impact. We don’t chase hype cycles. We innovate, build and deploy responsible AI which 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 Bringing medicine to patients is complex, expensive and high-risk. Faculty’s Life Science’s team is concentrated on building AI solutions which optimise the research and commercialisation of life-changing therapies. We partner with major pharma firms, academic research centres and MedTech start-ups to design and deliver solutions which address critical healthcare challenges, and help to democratise health for all. ABOUT THE ROLE: As a Senior Machine Learning Engineer, we’ll look to you to lead development and deployment of cutting-edge AI systems for our diverse clients. You’ll design, build, and deploy scalable, production-grade ML software and infrastructure that meets rigorous operational and ethical standards. This is an ambitious, cross-functional role requiring a blend of technical expertise, engineering leadership, and confident client-facing skills. WHAT YOU'LL BE DOING: - Leading technical scoping and architectural decisions for high-impact ML systems - Designing and building production-grade ML software, tools, and scalable infrastructure - Defining and implementing best practices and standards for deploying machine learning at scale across the business - Collaborating with engineers, data scientists, product managers, and commercial teams to solve critical client challenges and leverage opportunities - Acting as a trusted technical advisor to customers and partners, translating complex concepts into actionable strategies - Mentoring and developing junior engineers, actively shaping our team's engineering culture and technical depth WHO WE'RE LOOKING FOR: - You understand the full ML lifecycle and have significant experience operationalising models built with frameworks like TensorFlow or PyTorch - You bring deep expertise in software engineering and strong Python skills, focusing on building robust, reusable systems - You have demonstrable hands-on experience with cloud platforms (e.g., AWS, Azure, GCP), including architecture, security, and infrastructure - You've extensive experience working with container and orchestration tools such at Docker & Kubernetes to build and manage applications at scale - You thrive in fast-paced, high-growth environments, demonstrating ownership and autonomy in driving projects to completion - You communicate exceptionally well, confidently guiding both technical teams and senior, non-technical stakeholders THE INTERVIEW PROCESS 1. Talent Team Screen (30 minutes) 2. Pair Programming Interview (90 minutes) 3. System Design Interview (90 minutes) 4. Commercial Interview (60 minutes) OUR RECRUITMENT ETHOS We aim to grow the best team - not the most similar one. We know that diversity of individuals fosters diversity of thought, and that strengthens our principle of seeking truth. And we know from experience that diverse teams deliver better work, relevant to the world in which we live. We’re united by a deep intellectual curiosity and desire to use our abilities for measurable positive impact. We strongly encourage applications from peop