Machine Learning Engineer

Join to apply for the Machine Learning Engineer role at Faculty
.

Why Faculty?

We established Faculty in 2014 because we believed AI would be the most important technology of our time. Since then, we’ve worked with over 350 global customers to transform their performance through human‑centric AI. We don’t chase hype cycles; we innovate, build, and deploy responsible AI that moves the needle. Our business is growing fast, and we’re always looking for individuals who share our intellectual curiosity and want to build a positive legacy through technology.

Our Life Sciences team focuses on building AI solutions to optimise the research and commercialisation of life‑changing therapies. We partner with major pharma firms, academic research centres, and Med Tech start‑ups to design and deliver solutions that address critical healthcare challenges and help democratise health for all.

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.

• 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.

• You understand the full machine learning lifecycle and have experience ope rationalising models built with frameworks like Scikit‑learn, Tensor Flow, 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 have 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.

We aim to grow the best team – not the most similar one. Diversity of individuals fosters diversity of thought and strengthens our pursuit of truth. We strongly encourage applications from people of all backgrounds, ethnicities, genders, religions, and sexual orientations.

• Unlimited Annual Leave Policy
• Private healthcare and dental
• Enhanced parental leave
• Family‑Friendly Flexibility & Flexible working
• Sanctus Coaching
• Hybrid Working (2 days in our Old Street office, London)

If you don’t feel you meet all the requirements, but are excited by the role and know you bring some key strengths, please do apply or reach out to our Talent Acquisition team for a confidential chat – talent. We are open to conversations about part‑time roles or condensed hours.

• Entry level

• Full‑time

• Engineering and Information Technology

• Technology, Information and Internet