About the role
Join us as a Machine Learning Engineer to deliver bespoke, impactful AI solutions for our diverse Retail & Consumer 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 closely with clients and cross-functional teams, you’ll ensure the technical feasibility and successful delivery of high-quality, production-grade ML systems that drive tangible business outcomes.
What you’ll be doing
Building and deploying production-grade ML software, tools, and infrastructure.
Creating reusable, scalable solutions that accelerate the delivery of AI and machine learning systems across retail and consumer use cases.
Collaborating with engineers, data scientists, product teams, and commercial leads to solve critical client challenges.
Leading technical scoping and architectural decisions to ensure project feasibility, scalability, and commercial impact.
Defining and implementing Faculty’s standards for deploying machine learning systems in production.
Acting as a trusted technical advisor to customers and partners, translating complex ML concepts into actionable business outcomes.
Applying machine learning to challenges such as demand forecasting, customer analytics, personalisation, pricing, marketing optimisation, inventory management, and operational efficiency.
Supporting clients in adopting AI capabilities that improve customer experiences and drive sustainable growth.
Who we’re looking for
You understand the full machine learning lifecycle and have experience operationalising models built with frameworks such as 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 containerisation and orchestration tools such as Docker and Kubernetes to build and manage applications at scale.
You are comfortable with core ML concepts, including probability, statistics, experimentation, and common machine learning techniques.
Experience working with retail, consumer, ecommerce, marketing, supply chain, or customer data is beneficial but not essential.
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 challenging problems, and deliver impactful solutions.
Our interview process
Talent Team Screen (30 mins)
Pair Programming Interview (90 mins)
System Design Interview (90 mins)
Commercial Interview (60 mins)
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. We’re 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
If you don’t feel you meet all the requirements, but are excited by the role and know you bring some key strengths, please don't hesitate in applying as you might be right for this role, or other roles. We are open to conversations about part-time hours.
Machine Learning Engineer • London
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