Lead Quality Assurance Engineer - Machine Learning

At Hudl, we build great teams. We hire the best of the best to ensure you’re working with people you can constantly learn from. You’re trusted to get your work done your way while testing the limits of what’s possible and what’s next.

We work hard to provide a culture where everyone feels supported, and our employees feel it—their votes helped us become one of Newsweek's Top 100 Global Most Loved Workplaces . We think of ourselves as the team behind the team, supporting the lifelong impact sports can have: the lessons in teamwork and dedication; the influence of inspiring coaches; and the opportunities to reach new heights. That’s why we help teams from all over the world see their game differently.

Our products make it easier for coaches and athletes at any level to capture video, analyze data, share highlights and more. Ready to join us? Your Role Our Applied Machine Learning (AML) team’s vision is to extract valuable insights from video and deliver them to coaches, athletes, and fans at the perfect moment; serving over 230K sports teams across 40+ sports, including 11K+ professional teams.

We’re looking for a Lead Quality Assurance Engineer to join our AML Platform squad - the team that designs, builds, and operates our shared MLOps platform, reducing delivery friction, and acting as a force-multiplier for every squad we support. As the Lead QA Engineer, you’ll: Provide technical leadership. You’ll deliver quality leadership across the AML Platform Squad and broader AML organization, helping squads ship ML products faster, safer, and with greater confidence - from model development through to scaled inference.

Own the architecture and strategy. You will be hands-on in designing and building our quality infrastructure across the MLOps platform - architecting test frameworks, deployment safety tooling, and observability solutions - while owning the long-term technical strategy to ensure it scales with development speed. Collaborate across departments.

You’ll work across AML squads to drive alignment on quality initiatives from CI/CD pipeline standards to canary release patterns and hardware-in-the-loop testing, ensuring scalable platform solutions meet long-term strategic objectives. Build and deliver. You’ll be a hands-on contributor to the AML Platform Squad’s engineering work - writing code, designing systems, and implementing quality solutions - while ensuring long-term objectives stay aligned with reliable, efficient delivery.

Drive proactive quality. By anticipating risks across the ML product lifecycle - experimentation, deployment, inference, and observability - , you’ll identify and address potential obstacles to prevent issues before they ever reach production. Coach and mentor.

You’ll guide Software Engineers, Data Scientists, and QA practitioners on technical quality and innovation, fostering an environment where your teammates and the squads we support can grow and succeed. K. Must-Haves MLOps or platform engineering experience.

You have hands-on, practical experience designing and building shared ML platform tooling — experimentation infrastructure, model deployment pipelines, observability systems, or inference at scale. As you'd be the first QA in our ML team, this knowledge is essential. A proven leader.

You have experience leading complex quality initiatives across platform and product teams, with the ability to define strategy for shared infrastructure that serves multiple squads simultaneously. Technical expertise. You have a deep understanding of CI/CD pipelines, deployment safety patterns (canary, A/B, automated rollback), and a proactive approach to adopting new quality methodologies in ML and production engineering contexts.

An expert coach.