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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Machine Learning Engineer - **Company:** Relay Technologies - **Location:** London, UK - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** BigQuery, Cloud Engineering, Python (Programming Language), Machine Learning, Azure Machine Learning, Software Construction, System Testing, Delivery Pipeline, Kubernetes, Information Technology, ONNX (Open Neural Network Exchange) Format, Codebase, Machine Learning Operations - **Published:** July 24, 2026 - **Apply:** https://uk.indeed.com/viewjob?jk=f532f5d667dc37d9 ## About the Role * 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. ## Description * 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, * 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., * 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. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [What is relational learning and why does it matter?](https://www.wearedevelopers.com/videos/396-what-is-relational-learning-and-why-does-it-matter) - [Understanding Kubernetes in a visual way](https://www.wearedevelopers.com/videos/100085-understanding-kubernetes-in-a-visual-way) - [Getting to Know Your Legacy (System) with AI-Driven Software Archeology](https://www.wearedevelopers.com/videos/1437-getting-to-know-your-legacy-system-with-ai-driven-software-archeology) - [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning) - [Instant KAI Sandboxes with vCluster: Multi-Tenant, Multi-Scheduler GPU Sharing](https://www.wearedevelopers.com/videos/100333-instant-kai-sandboxes-with-vcluster-multi-tenant-multi-scheduler-gpu-sharing) ## Related Articles - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer)