Senior Machine Learning Engineer
Hybrid (London)Full-timePosted 10mo ago
About the role
Senior ML Engineer responsible for leading development and deployment of production-grade AI systems for diverse clients in Faculty's Life Sciences team, with a focus on scalable ML software and responsible AI.
Responsibilities
- 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
Qualifications
- Understanding the full ML lifecycle and significant experience operationalising models built with frameworks like TensorFlow or PyTorch
- Deep expertise in software engineering and strong Python skills, focusing on building robust, reusable systems
- Extensive experience with cloud platforms (e.g., AWS, Azure, GCP), including architecture, security, and infrastructure
- Experience with container and orchestration tools such as Docker & Kubernetes to build and manage applications at scale
- Ability to thrive in fast-paced, high-growth environments with ownership and autonomy
- Excellent communication skills, guiding both technical teams and senior, non-technical stakeholders
Skills
Required:ML lifecycle expertisePythonTensorFlow or PyTorchCloud platformsDocker & KubernetesCommunication
Last updated Oct 21, 2026. Interested? Apply on the company site.
About Faculty
Frontier AI for the frontlines of the world.
Faculty partners with organisations to enhance performance through cutting-edge artificial intelligence solutions, driving real-world impact.
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