About this role
Machine Learning Engineer (Safety) is a full-time position based in London, UK, that suits professionals looking to build scalable production-grade machine learning systems for high-stakes AI safety and national security missions. The role sits within the National Security and AI Safety business unit, bridging the gap between research and practical implementation.
Role Overview
The Machine Learning Engineer (Safety) at faculty works within the London office to deliver bespoke AI solutions for diverse clients across sectors such as government, finance, retail, energy, life sciences, and defence. This position focuses on building scalable production-grade machine learning systems and collaborating with frontier labs to provide robust AI safety red teaming and evaluation.
Key Responsibilities
Requirements
Skills and Tools
About the Company
Faculty was established in 2014 to develop human-centric artificial intelligence that transforms performance across global customers in government, finance, retail, energy, life sciences, and defence. The National Security and AI Safety business unit focuses on responsible AI development and deployment for global stability and security, partnering with government entities and technology organizations worldwide.
How to Apply
To apply for this position, please submit your application directly on the official faculty careers page.
Skills and tech stack
Questions candidates ask
Where is the job located?
The role is based in London, UK.
What programming language is required?
Strong Python skills are required for this position.
What frameworks must I have experience with?
You need experience operationalising models built with frameworks like Scikit-learn, TensorFlow, or PyTorch.
What does the interview process involve?
The interview process consists of a 30-minute talent team screen, a 90-minute pair programming interview, a 90-minute system design interview, and a 60-minute commercial interview.