Description
As a Senior Machine Learning Engineer at Faculty, you'll lead the development and deployment of cutting-edge AI systems for diverse clients.
Faculty is an organisation that leverages AI for the benefit of individual citizens and the public good, working closely with government clients.
In this role, you'll design, build, and deploy scalable, production-grade ML software and infrastructure that meets rigorous operational and ethical standards.
Responsibilities:
- Lead technical scoping and architectural decisions for high-impact ML systems
- Design and build production-grade ML software, tools, and scalable infrastructure
- Define and implement best practices and standards for deploying machine learning at scale across the business
- Collaborate with engineers, data scientists, product managers, and commercial teams to solve critical client challenges and leverage opportunities
- Act as a trusted technical advisor to customers and partners, translating complex concepts into actionable strategies
- Mentor and develop junior engineers, actively shaping the team's engineering culture and technical depth
Requirements:
- Understand the full ML lifecycle and have significant experience operationalising models built with frameworks like TensorFlow or PyTorch
- Bring deep expertise in software engineering and strong Python skills, focusing on building robust, reusable systems
- Have demonstrable hands-on experience with cloud platforms (e.g., AWS, Azure, GCP), including architecture, security, and infrastructure
- Extensive experience working with container and orchestration tools such as Docker & Kubernetes to build and manage applications at scale
- Thrive in fast-paced, high-growth environments, demonstrating ownership and autonomy in driving projects to completion
- Communicate exceptionally well, confidently guiding both technical teams and senior, non-technical stakeholders