AI/ML Engineer focusing on machine learning applications in oncology. Developing analytical solutions to enhance patient selection and drive next - generation assets in healthcare.
About the role
- Senior Machine Learning Engineer leading development and deployment of AI systems for various clients at Faculty. Focused on building scalable ML software and infrastructure.
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
Requirements
- 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.
Benefits
- Unlimited Annual Leave Policy
- Private healthcare and dental
- Enhanced parental leave
- Family-Friendly Flexibility & Flexible working
- Sanctus Coaching
- Hybrid Working (2 days in our Old Street office, London)
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
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