Senior Machine Learning Engineer (Safety)

The role

You will lead the development and deployment of cutting-edge AI systems for diverse clients. You will design, build, and deploy scalable, production-grade ML software and infrastructure.

What you will do

• Leading technical scoping and architectural decisions for high-impact ML systems and capability testing of Frontier AI models
• 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
• Acting as a trusted technical advisor to customers and partners
• Mentoring and developing junior engineers

Required qualifications

• Significant experience building and deploying secure and scalable LLM applications
• Comfortable with multi-agent harness tooling and AI Safety evaluation procedures
• Understand the full ML lifecycle
• Confident operationalising models built with frameworks like TensorFlow or PyTorch
• Deep expertise in software engineering
• Strong Python skills
• Hands-on experience with cloud platforms (e.g., AWS, Azure, GCP) specifically cloud architecture, infrastructure management, and end-to-end cybersecurity practices
• Extensive experience working with container and orchestration tools such as Docker & Kubernetes
• Ability to thrive in fast-paced, high-growth environments
• Exceptional communication skills to guide technical teams and senior, non-technical stakeholders

About the company

Faculty was established in 2014 to transform performance through human-centric AI. They work with over 350 global customers across government, finance, retail, energy, life sciences and defence.