Senior Machine Learning Engineer in London

Senior Machine Learning Engineer in London

London Full-Time 59400 - 72600 £ / year (est.) No working from home possible
Relay Technologies, Inc.

At a Glance

  • Tasks: Lead the production of machine learning models and enhance our ML platform.
  • Company: Relay, a fast-growing logistics startup backed by major investors.
  • Benefits: Competitive salary, inclusive culture, and opportunities for professional growth.
  • Other info: Dynamic environment focused on innovation and collaboration.
  • Why this job: Join a team reshaping e-commerce logistics with cutting-edge technology.
  • Qualifications: 2+ years in ML production and 4+ years in software development.

The predicted salary is between 59400 - 72600 £ per year.

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, Relay is scaling faster than 99.98% of venture-backed startups. We are 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 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 will:

  • 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 are 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.

Senior Machine Learning Engineer in London employer: Relay Technologies, Inc.

Relay is an exceptional employer, offering a vibrant and intellectually stimulating work culture that prioritises innovation and collaboration. As a Senior Machine Learning Engineer, you'll have the opportunity to work with cutting-edge technology in a fast-paced environment, while benefiting from a commitment to employee growth and development. With a focus on diversity and inclusion, Relay fosters a supportive atmosphere where your contributions are valued and impactful.

Relay Technologies, Inc.

Contact Details:

Relay Technologies, Inc. Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Senior Machine Learning Engineer in London

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We think you need these skills to ace Senior Machine Learning Engineer in London

Machine Learning
Python
Rust
Model Productionisation
Model Serving Architecture
Automated Releases
System Testing

Some tips for your application 🫡

Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.

Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Relay Technologies, Inc..

Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Relay Technologies, Inc. and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!

Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!

How to prepare for a job interview at Relay Technologies, Inc.

Brush Up on Your Coding Skills

For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.

Know Your Tools and Frameworks

Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Relay Technologies, Inc. uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.

Showcase Your Projects

Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.

Prepare for Behavioural Questions

While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.