Machine Learning Engineer

About the Team

Bringing medicine to patients is complex, expensive and high-risk. Faculty’s Life Science’s team is concentrated on building AI solutions which optimise the research and commercialisation of life-changing therapies.

We partner with major pharma firms, academic research centres and MedTech start-ups to design and deliver solutions which address critical healthcare challenges, and help to democratise health for all.

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're 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 at 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 delivery solutions