Machine Learning Engineer

Location: London - Hybrid Why Faculty?
We established Faculty in 2014 because we thought that 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 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 we're 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 you'll be empowered to envision its most powerful applications, and to make them happen.
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 democratize 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 operationalising models built with frameworks like Scikit-learn, TensorFlow, or PyTorch.
You possess strong Python skills and solid experience in software engineering best practices.
AWS, Azure, GCP), including architecture and security.
You are comfortable with core ML concepts, including probability, statistics, and common learning techniques.
We know that diversity of individuals fosters diversity of thought, and that strengthens our principle of seeking truth. Unlimited Annual Leave Policy
Private healthcare and dental
Enhanced parental leave
Family-Friendly Flexibility & Flexible working
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@faculty.ai Please know we are open to conversations about part-time roles or condensed hours.
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