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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Software Engineer, Machine Learning Services - **Company:** UiPath - **Location:** London, UK (Remote available) - **Experience:** Expert - **Salary:** £51,775.0 - **Contract:** Permanent contract - **Skills:** Abstraction Layers, Application Programming Interfaces (APIs), Amazon Web Services, Amazon S3, Microsoft Azure, C++ (Programming Language), Cloud Storage, Nvidia CUDA, Serialization, Data Structures, Distributed Systems, Hardware Interface Design, Python (Programming Language), Machine Learning, Message Broker, Performance Tuning, Queueing Systems, Azure Machine Learning, Multithreading, Cloud Platform System, Concurrency, Gpu Programming, Containerization, Uipath, Kubernetes, ONNX (Open Neural Network Exchange) Format, Machine Learning Operations, Asynchronous Programming, Api Gateway, Docker - **Published:** July 18, 2026 - **Apply:** https://www.adzuna.co.uk/jobs/details/5806150054 ## About the Role Our world is one of distributed systems, high-throughput model serving, and complex asynchronous training workflows. We're looking for a systems-level engineer who wants to work on the gnarly, foundational problems of a production ML platform. You'll support a system that handles a massive volume of inference requests and orchestrates unattended model training across a diverse landscape of model architectures. This isn't just about gluing APIs together; it's about building the infrastructure that makes it all possible.Our core platform is written in Rust for performance, correctness, and fearless concurrency. ML models and services are primarily in Python. If you're intrigued by the challenges of the software/hardware interface, OS-level optimization, and building robust, multi-tenant distributed systems, you'll fit right in, * A solid track record (5+ years) of engineering and architecting large-scale, distributed commercial services. Your experience speaks for itself. * Deep proficiency in a systems-level language (Rust, C++, Go). A willingness and curiosity to become an expert in Rust is essential, as it's the foundation of our core services. Strong Python skills are also critical. * Real-world experience with cloud ecosystems (Azure, AWS, or GCP) and containerization (Docker, Kubernetes). You should understand how production systems are deployed, monitored, and scaled. * A firm grasp of concurrency, multithreading, and asynchronous programming. You know the difference between a mutex and a channel, and you know when (and when not) to use them. * A pragmatic understanding of computer science fundamentals. We care more about your ability to solve real-world problems with data structures and algorithms than your ability to recite them from a textbook. * An opinion on what makes good code and good architecture, and the ability to articulate it. You should be comfortable challenging assumptions (including our own) and contributing to a culture of continuous improvement. * You're a builder and a problem-solver at heart. * You've already worked with Rust in a production environment. * Experience with MLOps, particularly the challenges of managing the lifecycle of models in a multi-tenant, high-availability system. * Familiarity with building ML inference services, model serialization (e.g., ONNX), and GPU programming (CUDA). * You've built or worked on custom storage or job-queueing systems before and have the scars to prove it. ## Description We're the Machine Learning Services (MLS) team at UiPath-a small, sharp group of senior engineers building the core platform that powers UiPath's large-scale AI and Document Understanding products., * Design, build, and operate the core MLS platform. This includes our Rust-based API gateway, Python ML compute workers, and the distributed job queue that orchestrates it all. * Solve hard concurrency, performance, and distributed systems problems to ensure our platform is bulletproof for high-volume production workloads. * Work directly with product and ML science teams to understand their needs and build the scalable infrastructure required to bring their models to life-from massive GenAI models to fine-tuned, specialized classifiers. * Develop our custom-built, content-addressable storage abstraction layer over cloud object stores (GCS, S3, Azure Blob), complete with its own garbage collection and sharding logic. * Enhance our asynchronous job-queueing system, built from the ground up on the storage layer using compare-and-swap primitives for atomicity. No off-the-shelf message broker could handle our specific needs. * Dive deep into the entire stack, from Kubernetes and container orchestration, through gRPC-based service communication, to the performance tuning of ONNX-based inference on GPU-accelerated hardware. * Write clean, efficient, and rigorously tested code. We value simplicity, correctness, and peer review. ## Related Videos - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [How to achieve web automation with UiPath](https://www.wearedevelopers.com/videos/310-how-to-achieve-web-automation-with-uipath) - [WeAreDevelopers LIVE - CSS is DOOMed](https://www.wearedevelopers.com/videos/1838-wearedevelopers-live-css-is-doomed) - [The state of MLOps - machine learning in production at enterprise scale](https://www.wearedevelopers.com/videos/369-the-state-of-mlops-machine-learning-in-production-at-enterprise-scale) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) - [Shipping Faster with Less: Render on Cloud Hosting, AI Workloads, and the Future of DevOps](https://www.wearedevelopers.com/videos/1894-shipping-faster-with-less-render-on-cloud-hosting-ai-workloads-and-the-future-of-devops) ## 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) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Building AI Solutions with Rust and Docker](https://www.wearedevelopers.com/magazine/494-building-ai-solutions-with-rust-and-docker) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models)