Machine Learning Engineer

Faculty is a pioneering AI company that transforms organizational performance through safe and human-centric AI solutions. As a Machine Learning Engineer, you'll join their Government & Public Services team, working on high-impact problems while designing and deploying production-grade ML systems.

The role offers a hybrid working model, splitting time between client locations, Faculty's Old Street office, and remote work. You'll be at the forefront of operationalizing machine learning, working with cutting-edge ML applications and developing new methodologies for managing AI systems at scale.

The position requires someone who can bridge the gap between engineering and machine learning, working closely with data scientists to deploy trained models into production environments. You'll be using modern tools like Docker, Kubernetes, and major cloud platforms, while adhering to software engineering best practices in Python development.

What makes this role unique is the opportunity to work with over 300 global customers, alongside experts from government, academia, and tech giants. You'll be essential in building reusable, scalable tools and implementing best practices for ML operations. The role requires security clearance eligibility due to work in the National Security space.

Faculty offers a dynamic environment where you'll be surrounded by brilliant minds and driven by intellectual curiosity. The team is diverse, coming from various professional backgrounds, united by the goal of solving the biggest challenges in applied AI. This is an opportunity to shape the future of AI implementation while working with some of the brightest minds in the field.

The ideal candidate combines technical expertise with a scientific mindset, pragmatic problem-solving abilities, and excellent communication skills. You'll have the autonomy to take ownership of problems and see them through to execution, while contributing to Faculty's mission of bringing Frontier AI to the frontlines of the world.