Machine Learning Engineer

About Faculty At Faculty we transform organisational performance through safe, impactful and human‑centric AI. With more than a decade of experience we provide over 350 global customers with bespoke AI consulting and Fellows from our award‑winning Fellowship programme. Our expert team brings together leaders from across government, academia and global tech giants to solve the biggest challenges in applied AI. Should you join us you’ll have the chance to work with and learn from some of the brilliant minds who are bringing frontier AI to the frontlines of the world. About the team Our Defence team is focused on building and embedding human‑centred AI solutions that give our nation a competitive edge in the defence sector. We collaborate with our clients to bring ethical, reliable and cutting‑edge AI to high‑stakes situations, and maintain the balance of global powers essential to our liberty. Because of the nature of the work we do with our Defence clients you will need to be eligible for UK Security Clearance (SC) and be willing to work up to three days per week on site with these customers, which may require travel to locations outside of our London base. About the role Join us as a Machine Learning Engineer to deliver bespoke impactful AI solutions for our diverse clients. You will be instrumental in bringing machine learning out of the lab and into the real world, contributing to scalable software architecture and defining best practices. Working with clients and cross‑functional teams you’ll ensure technical feasibility and timely delivery of high‑quality production‑grade ML systems. What you’ll be doing Building and deploying production‑grade ML software tools and infrastructure. Creating reusable scalable solutions that accelerate the delivery of ML systems. Collaborating with engineers, data scientists and commercial leads to solve critical client challenges. Leading technical scoping and architectural decisions to ensure project feasibility and impact. Defining and implementing Faculty’s standards for deploying machine learning at scale. Acting as a technical advisor to customers and partners, translating complex ML concepts for stakeholders. Who we are looking for You understand the full machine learning lifecycle and have experience operationalising models built with frameworks like Scikit‑learn, TensorFlow or PyTorch. You possess strong Python skills and solid experience in software engineering best practices. You bring hands‑on experience with cloud platforms and infrastructure (e.g. AWS, Azure, GCP), including architecture and security. You’ve worked with container and orchestration tools such as Docker & Kubernetes to build and manage applications at scale. You are comfortable with core ML concepts including probability, statistics and common learning techniques. You’re an excellent communicator able to guide technical teams and confidently advise non‑technical stakeholders. You thrive in a fast‑paced environment and enjoy the autonomy to own scope, solve and deliver solutions. Our Interview Process Talent Team Screen (30 minutes) Pair Programming Interview (90 minutes) System Design Interview (90 minutes) Commercial Interview (60 minutes) What we can offer you The Faculty team is diverse and distinctive, and we all come from different personal, professional and organisational backgrounds. We have one thing in common: we are driven by a deep intellectual curiosity that powers us forward each day. Faculty offers the professional challenge of a lifetime. You’ll be surrounded by an impressive group of brilliant minds working to achieve our collective goals. Our consultants, product developers, business development specialists, operations professionals and more all bring something unique to Faculty, and you’ll learn something new from everyone you meet. Employment Type: Full‑Time Experience: \[years\] Vacancy: 1 #J-18808-Ljbffr