Machine Learning Engineer

Faculty; Greater London; On-site; GBP 70,000 - 110,000; Full time

Benefits offered by this job

Unlimited Annual Leave Policy

Private healthcare and dental

Enhanced parental leave

Family-Friendly Flexibility & Flexible

Sanctus Coaching

Hybrid Working

Job summary

Faculty is seeking a Machine Learning Engineer to deliver bespoke AI solutions for Retail & Consumer clients. You will bring ML from research to production, shaping scalable software architecture and best practices.

You’ll work with clients and cross-functional teams to ensure deliverables are production-ready and impactful. Join a team that values technical excellence and practical deployment, with opportunities to influence AI adoption across industries and enjoy a hybrid working model in the

Qualifications

• Experience with the full ML lifecycle and productionising models.
• Proficiency with Scikit-learn, TensorFlow or PyTorch.
• Strong Python skills and software engineering practices.
• Experience with cloud platforms (AWS/Azure/GCP) and containerisation.
• Ability to translate ML concepts into actionable business outcomes.

Responsibilities

• Build and deploy production-grade ML software, tools, and infrastructure.
• Create reusable, scalable solutions for AI/ML across retail and consumer use cases.
• Collaborate with engineers, data scientists, product teams, and commercial leads to solve client challenges.
• Lead technical scoping and architectural decisions for feasibility and scalability.
• Define and implement Faculty's standards for deploying ML systems in production.
• Act as trusted technical advisor translating ML concepts to business outcomes.
• Apply ML to demand forecasting, customer analytics, personalization, pricing, marketing optimisation, inventory management, and ops efficiency.
• Support clients in adopting AI capabilities to improve customer experiences and growth.

Skills

ML lifecycle

Python

Scikit-learn

TensorFlow

PyTorch

Cloud platforms (AWS/Azure/GCP)

Software engineering practices

Communication skills

Tools

Docker

Kubernetes

Job description

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. You can read about our real-world impact here.

We don’t 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 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.

About the team

In our Retail & Consumer Business Unit, we bring everything we have learned in more than a decade of Applied AI and use it to help leading retailers, consumer brands, marketplaces, and digital commerce businesses navigate a rapidly evolving landscape.

We develop and embed AI solutions that help organisations better understand their customers, optimise operations, improve forecasting and decision-making, and unlock new opportunities for growth. From supply chains and merchandising to marketing, personalisation, and customer experience, we work with clients to deliver measurable commercial impact through AI. We are proud to combine technical excellence with practical deployment, ensuring solutions create value in complex, real-world environments.

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