MLOps Engineer

Why Faculty

We established Faculty in 2014 because we thought that AI would be the most important technology of our time. Since then weve worked with over 350 global customers to transform their performance through human-centric AI. You can read about our real-world impact here.

We dont chase hype cycles. We innovate build and deploy responsible AI which moves the needle - and we know a thing or two about doing it well. We bring an unparalleled depth of technical product and delivery expertise to our clients who span government finance retail energy life sciences and defence.

Our business and reputation is growing fast and were always on the lookout for individuals who share our intellectual curiosity and desire to build a positive legacy through technology.

AI is an epoch-defining technology join a company where youll be empowered to envision its most powerful applications and to make them happen.

About the Team

Bringing medicine to patients is complex expensive and high-risk. Facultys Life Sciences 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 MLOps 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 youll ensure technical feasibility and timely delivery of high-quality production-grade ML systems.

What youll 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 Facultys standards for deploying machine learning at scale.

• Acting as a technical advisor to customers and partners translating complex ML concepts for stakeholders.

Who were 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.

• Youve 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.

• Youre 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 Interview Process

1. Talent Team Screen (30 minutes)

2. Pair Programming Interview (90 minutes)

3. System Design Interview (90 minutes)

4. Commercial Interview (60 minutes)

Our Recruitment Ethos

We aim to grow the best team - not the most similar one. We know that diversity of individuals fosters diversity of thought and that strengthens our principle of seeking truth. And we know from experience that diverse teams deliver better work relevant to the world in which we live. Were united by a deep intellectual curiosity and desire to use our abilities for measurable positive impact. We strongly encourage applications from people of all backgrounds ethnicities genders religions and sexual orientations.

Some of our standout benefits:

• 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 dont feel you meet all the requirements but are excited by the role and know you bring some key strengths please dont hesitate in applying as you might be right for this role or other roles. We are open to conversations about part-time hours.

Required Experience:

IC