Machine Learning Engineer

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 software, bespoke AI consultancy, 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.

Bringing medicine to patients is complex, expensive and high‑risk. Faculty’s Life Science 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.

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.

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• 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.
  

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• 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 delivery solutions.
  

The Faculty team is diverse and distinctive, and we all come from different personal, professional and organisational backgrounds. We all have one thing in common: we are driven by a deep intellectual curiosity that powers us forward each day.

Faculty is 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.