Staff Software Engineer (ML QA)

Job Summary

Applicants for this role should have strong experience designing, developing, and maintaining high-quality software systems. The role focuses on testing and validating a complex machine learning software stack, with particular emphasis on software architecture, automation, and engineering best practices. The ideal candidate is an experienced software engineer who values code quality, testability, and long-term maintainability, and enjoys building systems that other engineers rely on. This person will be comfortable working across large codebases, contributing to CI/CD infrastructure, and shaping technical direction through thoughtful design and mentoring in a technically demanding environment spanning ML frameworks, infrastructure, and AI accelerator hardware

The Team

The ML QA team is composed of highly skilled software engineers with a strong focus on automation, software quality, and data-driven validation. The team works closely with industry-standard machine learning frameworks and models, contributing to upstream open-source projects and collaborating across the wider software organization. Operating in a fast-paced environment, the team plays a critical role in ensuring reliability, performance, and maintainability across the ML software stack, helping to deliver robust and high-quality products to customers. ## Responsibilities and Duties

• Design, implement, and maintain robust test infrastructure and automation for a complex ML software stack. - Architect and evolve test frameworks and tooling with a focus on scalability, maintainability, and developer experience. - Build and maintain CI/CD pipelines targeting simulators, emulators (e.g. QEMU), and physical hardware. - Create representative ML workloads and gain insights from their execution. (Numerical accuracy, performance analysis and benchmarking). - Work closely with all Software development teams, supporting a culture of quality, security and maintainability. - Review code and designs, setting a high bar for software engineering best practices. - Mentor and support junior engineers, helping raise the overall technical capability of the team. - Evaluate existing test strategies and infrastructure, identifying gaps and driving improvements aligned with team and organizational goals. ##