Principal Machine Learning Scientist, Recommender Systems at Relay

Relay is fundamentally reshaping how goods move in an online era. Backed by Europe’s largest-ever logistics Series A ($35M) led by deep-tech investors Plural, and a recently closed Series B ($95M), Relay is scaling faster than 99% of venture-backed startups. We're assembling the most talent-dense team the logistics industry has ever seen

Relay’s Mission is to free commerce from friction. Today, high delivery costs act as a hidden tax on e-commerce, quietly shaping what can be sold online and limiting who can participate. We envision a world where more goods move more freely between more people, making the online shopping experience seamless and accessible to everyone.

THE TEAM
• ~160 people, around half in engineering, product and data
• 45+ advanced degrees across computer science, mathematics and operations research
• Thousands of data points captured, calculated, analysed and predicted for every single parcel we handle
• An intellectually vibrant culture of first‑principles thinking, tight feedback loops and relentless experimentation

Every courier who works with Relay chooses their day. A day is a set of routes that have to fit together, and every courier's ideal day competes with everyone else's. Work is finite and every route still has to be covered, so matching thousands of couriers to the work they want is a recommendation problem with few precedents.

Science at Relay is the brain of the operation: machine learning, operational research, recommender systems, causal inference, location intelligence and experimentation, working together to decide how every parcel gets delivered. There's no existing recommender to iterate on. You'll build it.

Recommender Systems Highlights

The Opportunity

As a Principal Machine Learning Scientist at Relay, you'll:

We're looking for candidates who…

Don't tick every box? If this problem excites you, we'd still love to hear from you.

Who Thrives at Relay?

Relay is an equal-opportunity employer committed to diversity, inclusion, and fostering a workplace where everyone thrives.

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