Faculty
Machine Learning Engineer
London, Remote. Posted a month ago
The role
You will build and deploy production-grade ML software, tools, and infrastructure. You will work with clients and cross-functional teams to deliver scalable AI solutions.
What you will do
- 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.
Required qualifications
- Understand the full machine learning lifecycle.
- Experience operationalising models built with frameworks like Scikit-learn, TensorFlow, or PyTorch.
- Strong Python skills.
- Solid experience in software engineering best practices.
- Hands-on experience with cloud platforms and infrastructure (e.g., AWS, Azure, GCP), including architecture and security.
- Worked with container and orchestration tools such at Docker & Kubernetes to build and manage applications at scale.
- Comfortable with core ML concepts, including probability, statistics, and common learning techniques.
- Excellent communicator, able to guide technical teams and confidently advise non-technical stakeholders.
- Thrive in a fast-paced environment.
- Enjoy the autonomy to own scope, solve and delivery solutions.
Before you apply
- You may need to be eligible for UK Developed Vetting (DV).
- Talent Team Screen (30 minutes).
- Pair Programming Interview (90 minutes).
- System Design Interview (90 minutes).
- Commercial Interview (60 minutes).
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.