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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # ML Integration and Test Development Engineer - **Company:** Arm Limited - **Location:** Cambridge, UK - **Salary:** £97,300.0 - £131,700.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Data Analysis, Automation of Tests, C++ (Programming Language), Compilers, Code Review, Continuous Integration, Software Debugging, Linux, Embedded Software, Github, Python (Programming Language), Machine Learning, Performance Tuning, Tensorflow, Software Engineering, Performance Testing, Pytorch, Gitlab, Hardware Acceleration, Machine Learning Operations, Software Version Control, Docker, Jenkins - **Published:** October 3, 2026 - **Apply:** https://www.totaljobs.com/job/integration-test-engineer/arm-job108076922 ## About the Role We are looking for an experienced software/hardware engineer with a strong analytical approach to join the team and help ensure the best quality with most recent Arm ML software, systems and IP. The successful engineer will be highly flexible, quick to learn and be motivated by the opportunity to understand and improve the quality of future Machine Learning solutions using Arm technology., * We're looking for someone who follows up when something seems off, takes ownership beyond their assigned tasks, and pushes past team limitations to drive the right outcome. * Actively use the latest AI tools and technologies to improve development, testing, and problem-solving. * Great python knowledge is essential. * Comfortable developing on Linux or Mac * You have experience working with SW development or automated testing. * You have strong communication skills, inter-cultural awareness and you embrace diversity. "Nice To Have" Skills and Experience : * Experience from building test infrastructure * Experience working with pre-silicon platforms. * Familiarity with Docker and CI/CD systems (Jenkins, GitLab, or GitHub). * Understanding of ML frameworks, compilers, or model execution flows. * Familiarity with data analysis., We're particularly interested in experience with: * Professional C++ development and complex software systems. * Machine Learning frameworks or tooling such as PyTorch. * Python for software development, ML tooling, testing or automation. * Debugging, performance analysis and solving complex software problems. * Collaborative software development using source control, code review, testing and continuous integration. Experience across every part of the ML software stack isn't expected. Knowledge of ML compilers, PyTorch internals, runtimes, drivers, embedded software, performance optimisation or hardware acceleration would be valuable, but we encourage applications from people whose experience doesn't cover every area. ## Description As an ML Engineer you will develop test infrastructure for our fully automated test flow, including functional and performance testing, as well as visualisation and report generation of the results. We use advanced pre-silicon platforms of next-generation systems, to understand new use-cases and significant workloads to ensure Arm IP and systems deliver excellent ML performance and quality., Our ML Engineering teams are looking for experienced software engineers with strong C++ skills and practical experience with Machine Learning frameworks such as PyTorch. The work sits at the intersection of Machine Learning, software and hardware. Projects span ML frameworks and compilers, runtimes, drivers, embedded software and performance optimisation, creating opportunities to work on complex engineering challenges across the ML software stack. We're hiring across several levels of seniority, with scope and technical leadership matched to experience. Interested in understanding what happens below an ML framework? Curious about how software and hardware come together to make AI workloads faster and more efficient? This could be a great opportunity to explore both. What You'll Do The team develops and optimises C++ and Python software for Machine Learning workloads, working closely with ML software and hardware engineers to understand how models execute and where performance and efficiency can be improved. The work could include ML compilation, PyTorch integration, runtimes and drivers, performance analysis or embedded software. There will also be opportunities to contribute to technical design, take ownership of larger engineering challenges and support the development of other engineers. ## Related Videos - [Docker network without Docker](https://www.wearedevelopers.com/videos/1418-docker-network-without-docker) - [Docker does that? 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