At a Glance
- Tasks: Lead the production of machine learning models and enhance our ML platform.
- Company: Join Relay, a fast-growing logistics startup backed by major investors.
- Benefits: Competitive salary, inclusive culture, and opportunities for professional growth.
- Other info: Dynamic team environment focused on innovation and collaboration.
- Why this job: Make a real impact in reshaping e-commerce logistics with cutting-edge technology.
- Qualifications: 2+ years in deploying models and 4+ years in software development.
The predicted salary is between 60000 - 80000 £ per year.
Relay is fundamentally reshaping how goods move in an online era. Backed by Europe's largest-ever logistics Series A ($35M), 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 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.
Relay is an equal-opportunity employer committed to diversity, inclusion, and fostering a workplace where everyone thrives.
Senior Machine Learning Engineer employer: Relay
Relay is an exceptional employer, offering a vibrant and intellectually stimulating work culture that prioritises creativity and collaboration. As a Growth Marketing Manager, you'll have the unique opportunity to drive impactful marketing strategies in a fast-paced environment, backed by significant investment and a mission to revolutionise logistics. With a commitment to employee growth and a focus on diversity and inclusion, Relay empowers its team members to innovate and excel while contributing to a meaningful cause.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Machine Learning Engineer
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Relay or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Relay.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like Relay.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like Relay that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace Senior Machine Learning Engineer
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.
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 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
✨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 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.