Senior Machine Learning Engineer

About the role

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 parcel Relay handles is touched by ML. We recommend and optimise route assignment, predict delivery durations, estimate parcel dimensions and weight, detect objects in images on device, forecast demand and decide network handovers. That's 10+ models running in the critical path of a live logistics network where quality is non-negotiable.

ML Stack Highlights

- Python and Rust. We keep things simple but use the right tool for the job

- Rust with ONNX in-process model execution where throughput is critical

- Chalk.ai http://Chalk.ai as our Feature Store

- GCP Agent Platform Endpoints for model serving

- Cloud-native on GCP. Services run on Kubernetes, with extensive use of BigQuery

The Opportunity

As a Senior Machine Learning Engineer at Relay, you'll:

- Own critical part of ML: productionising of our models end-to-end, from training pipeline through live integration to measured business impact.

- Build and mature our ML Platform. Evolve the model serving architecture, expand reusable components adoption and set the standards for how Relay ships ML org-wide.

- Strengthen existing models by architecting integration and system testing within training pipelines, automated releases and drift monitoring.

- Launch completely revamped processes side by side with data scientists and measure their real-world impact on the network.

We're looking for candidates who…

- Have at least two years deploying and operating models in production and four years building software on high-performing teams.

- Are comfortable diving into unfamiliar codebases and languages to ship a model into a live system.

- Prefer building the automation that removes manual labour over repeating it.

Who Thrives at Relay?

- Aim with Precision: You define problems clearly and measure your impact meticulously.