Senior Machine Learning Engineer

Stack

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
• ▹Act as a trusted technical advisor to customers and partners, translating complex concepts into actionable strategies
• ▹Mentor and develop junior engineers, shaping the team's engineering culture and technical depth

Requirements

• ▹Understanding of the full ML lifecycle, with significant experience operationalising models built with TensorFlow or PyTorch
• ▹Deep expertise in software engineering and strong Python skills, focused on building robust, reusable systems
• ▹Demonstrable hands-on experience with cloud platforms (AWS, Azure, GCP), including architecture, security, and infrastructure
• ▹Extensive experience with container and orchestration tools such as Docker and Kubernetes, building and managing applications at scale
• ▹Thrives in fast-paced, high-growth environments, with strong ownership and autonomy driving projects to completion
• ▹Exceptional communication skills, confidently guiding both technical teams and senior, non-technical stakeholders

Soft skills

What we offer

• ▹Unlimited annual leave
• ▹Private healthcare and dental cover
• ▹Enhanced parental leave
• ▹Family-friendly flexibility and flexible working
• ▹Sanctus coaching
• ▹Hybrid working

About the company

Founded in 2014, Faculty is a human-centric AI company that has worked with over 350 global customers across government, finance, retail, energy, life sciences and defence. This role sits within Faculty's Professional and Financial Services unit, which draws on over a decade of Applied AI experience to help financial institutions become more efficient and enhance customer experience within a highly regulated industry.