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Senior Machine Learning Engineer

Relay
Full TimeseniorHybrid
London - HybridPosted Yesterday

Role Overview

Relay is hiring a Senior Machine Learning Engineer. This is a full-time hybrid role, based in London - Hybrid. Part of Relay's Data Science hiring, posted yesterday. Full responsibilities, required qualifications, and the apply link are listed in the description below.

Salary Context

Salary is not disclosed in this posting. Market median for Senior-level Data Science roles is $160k-$214k (based on 97 comparable listings). Many employers share specifics during the interview process or after an initial screen.

Resume Keywords to Include

Make sure these keywords appear in your resume to improve ATS scoring

PythonRustGCPKubernetesBigQueryDriftPipelineTax

Job description

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 (whose portfolio spans fusion energy and space exploration), Relay is scaling faster than 99.98% 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

  • ~110 people, more than 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.
  • Play to Win: You chase bold bets, tackle the hard stuff, and view constraints as fuel, not friction.
  • 1% Better Every Day: You believe that small, consistent improvements lead to exponential growth. You move quickly, deliver results, and learn from every experience.
  • All In, All the Time: You show up and step up. You take ownership from start to finish and do what it takes to deliver when it counts.
  • People-Powered Greatness: You invest in your teammates. You give and receive feedback with care and candour. You build trust through high standards and shared success.
  • Grow the Whole Pie: You seek out win-win solutions for merchants, couriers, and our customers, because when they thrive, so do we.

If these resonate, and you combine strong technical fundamentals with entrepreneurial drive, let’s connect.

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

About Relay

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Relay

relaypro.com

Data ScienceHybrid

Frequently Asked Questions

How do I apply for the Senior Machine Learning Engineer position at Relay?

Use the Apply button above to submit your application directly to Relay. Most applications take less than 5 minutes if your resume and contact details are ready, and you'll be routed to the employer's official application system to finish.

Is the Senior Machine Learning Engineer role at Relay remote or in-office?

This is a hybrid role based in London - Hybrid. Expect a mix of in-office and remote days, with the specific cadence set by the hiring manager.

What does a Senior Machine Learning Engineer at Relay earn?

Relay has not disclosed a salary range in this posting. Many employers share specifics later in the interview process; you can also ask during a recruiter screen if compensation transparency is important to you.

When was the Senior Machine Learning Engineer role at Relay posted?

This role was posted on July 22, 2026 (yesterday). It's still listed as actively hiring; we re-confirm openings against the source system multiple times per day and remove closed roles.

How much experience does the Senior Machine Learning Engineer role at Relay require?

This is a senior-level position. Most senior roles call for 5+ years of directly relevant experience. Relay lists their specific requirements in the description below, so review the must-have qualifications closely before applying.

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