TL;DR

Tilt is at the forefront of commerce, building a net-new way to buy and sell online. As we enter our next phase of growth, we’re rebuilding the CEO Office and seeking a Machine Learning Engineer to work on personalisation at Tilt.

This is a rare opportunity for someone to take our recommendation systems from 1 to 100. You will work on building real-time algorithms for high conversion across a video-first shopping platform that sits in its own class.

You must be comfortable building feature pipelines, training models, deploying, and monitoring.

About Tilt

Tilt’s mission is simple: Make Commerce Alive.

From static store website builders to impersonal marketplaces, today's ecosystem is aging fast. It was built for transactional experiences, not for the new generation of merchants who grow through attention, community and personality.

In the UK alone, millions of shoppers, from sneakerheads and Y2K girlies to collectors and parents, have signed up to Tilt. Our platform has helped sellers go from zero to £1M+ in earnings, and hundreds more earn above the UK median income.

And we are just getting started.

Your Mission

You will own and build solutions for personalisation across different surfaces in our app, including live streams, products, videos, and more.

1. Learn about our users, explore the data and engineer powerful signals

2. Deliver ML algorithms which significantly outperform our current heuristic models

3. Make Tilt the world leader in real-time recommendations & agentic personalisation

As an AI/ML engineer, you will work closely with our Platform and Growth teams. There will be close collaboration with product, engineering and the business team, and for the near term, you will be the only AI/ML engineer at Tilt. To be successful, you must be comfortable tackling a wide range of technical challenges.

Location: Hybrid (3 days a week from London, King’s Cross office - mandatory days Tuesdays & Thursdays plus one day of your choice!)

What You’ll Do

0 to 3 months

• Dive deep into the product and data to learn what the best personalisation experience is for customers and our business

• Rapidly onboard onto the existing recommendations system, identifying key improvements and implementing them

• Transition us from a scoring model to a more robust ML model

• Integrate novel new features and real-time signals into the recommendation engine

3+ months

• Continue to ensure we are serving best-in-class recommendations for our customers

• Extend the recommendation system to more experiences in our app

• Integrate into our search experience, working with the broader team to invent a new type of search

Who You Are

• An ML and AI enthusiast, you’ve built recommendation & ranking systems in production, not just research prototypes

• A builder: You can code and think in systems

• A scientist: You have strong foundations in data, statistics and machine learning

• An excellent communicator: Written, verbal and visual communication are superhuman strengths; you must be exceptional at at least 2 of these

• Autonomous: You do not require close supervision; you spot problems and solve them

• Comfortable operating in ambiguity, pressure, and high-expectation environments

Nice to Have