About this role
This position suits professionals with a strong background in software engineering and machine learning who want to build production-grade AI systems in London. Faculty is hiring a Machine Learning Engineer based in London, UK, to deliver bespoke artificial intelligence solutions for diverse clients, particularly within the energy, transition, and environment sector.
Role Overview
As a Machine Learning Engineer at Faculty, the chosen professional will operationalize models and transition machine learning out of the laboratory and into real-world applications. The role involves contributing to scalable software architecture, defining deployment best practices, and collaborating with cross-functional teams to ensure the timely delivery of high-quality systems for clients across various industries.
Key Responsibilities
Requirements
Skills and Tools
About the Company
Faculty was established in 2014 to build responsible artificial intelligence that transforms client performance. The company partners with global customers spanning government, finance, retail, energy, life sciences, and defence. Its Energy, Transition and Environment business unit works with major energy operators, GreenTech startups, and national infrastructure providers to accelerate the transition to net-zero emissions.
How to Apply
Interested candidates should apply directly on the official Faculty careers page.
Skills and tech stack
Questions candidates ask
Where is the Machine Learning Engineer role located?
The position is based in London, UK.
What industries does the hiring team focus on?
The Energy, Transition and Environment business unit focuses on the clean energy revolution, partnering with major energy operators, GreenTech startups, and national infrastructure providers.
What technical frameworks and tools are required?
Candidates need experience with Python, software engineering best practices, cloud platforms like AWS, Azure, or GCP, container tools such as Docker and Kubernetes, and ML 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.
Are alternative work arrangements available?
The company is open to conversations about part-time hours.