Job Title
Senior Machine Learning Engineer
Salary
£110k-£130k
Company Description
Faculty is an established London-based AI consultancy founded in 2014 that has delivered human-centric AI solutions to over 350 global customers. Specializing in high-impact sectors like government, finance, and life sciences, they focus on building responsible, production-grade technology that solves complex real-world challenges for organizations worldwide.
Job Description
Join Faculty’s Life Sciences team to lead the development of production-grade AI systems for pharma and MedTech leaders. You will own the full ML lifecycle – from technical scoping and architecture to deployment and monitoring. This hybrid London role balances deep engineering with client advisory to deliver AI solutions that accelerate life-changing healthcare therapies.
Location
London, UK
Why this role is remarkable
- Lead high-impact projects within the Life Sciences sector, partnering with major pharma firms and MedTech startups to optimize the commercialization of life-changing therapies.
- Own the entire path from model to monitored production system, exercising significant autonomy over architectural decisions and deployment standards across the business.
- Join a mature, intellectually curious culture at one of the UK’s most respected AI consultancies with a decade-long track record of success.
What You Will Do
- Lead technical scoping and architectural decisions for scalable, production-grade machine learning systems meeting rigorous ethical and operational standards.
- Design and build robust ML software and infrastructure using Python, Docker, and Kubernetes across major cloud platforms like AWS, Azure, or GCP.
- Act as a trusted technical advisor to senior stakeholders, translating complex AI concepts into actionable strategies that solve critical healthcare challenges.
The ideal candidate
- Significant experience operationalizing models built with TensorFlow or PyTorch, transitioning them from training environments into monitored, live production systems.
- Expert-level Python software engineering skills with a focus on building reusable systems and a deep understanding of cloud infrastructure and containerization.
- Excellent communication skills with the ability to guide both technical teams and non-technical client stakeholders through complex architectural trade-offs.
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