Ground every answer in facts on this page and the original listing. We never invent Glassdoor-style reviews or salaries that are not in our data.
Prepare stories on leading QA for complex systems, designing tests for nondeterministic ML behavior, risk-based prioritization, and mentoring. Expect system-design-style quality discussions and practical test-case or automation exercises.
Strong fit if you have led QA for software with ML components, can set standards without inventing process theater, and want on-site work in London at Hudl. Thin public data means validate culture, tooling, and level directly with the hiring team.
As Lead Quality Assurance Engineer – Machine Learning at Hudl, expect to own test strategy for ML-backed features: define quality bars for models and data pipelines, design automated regression and evaluation suites, partner with engineering and data science on release gates, triage production issues, and coach other QAs on ML-specific risk (data drift, label quality, latency, and fairness checks).
Prioritize automated testing (API/UI/performance), Python or similar for eval harnesses, CI/CD, observability, and ML basics (datasets, metrics, offline vs online evaluation). No certification resources were supplied for this listing.
The listing marks remote as no; treat it as London-based unless Hudl states otherwise.
Quality work typically covers model and pipeline behavior, evaluation metrics, data issues, and safe rollouts—not only classic UI checks.
Start at hudl.com and the official careers pages; this enricher does not add unstated salary or review scores.
Website: hudl.com
Public cache only — not an employee review.
Lead Quality Assurance Engineer - Machine LearningHudlLondon, UKFull Time, No Remote What This Role Involves In this role, you will be responsible for leading the quality assurance efforts of Hudl’s Applied Machine Learning (AML) team. You will ensure that our products deliver reliable and consistent insights to coaches, athletes, and fans. Your responsibilities include developing and maintaining test strategies, creating automated testing frameworks, and collaborating with cross-functional teams to improve product quality. What You'll Do Develop comprehensive test plans for AML products, ensuring they meet the highest standards of reliability and accuracy. Create and maintain robust automated testing frameworks to streamline the testing process and reduce manual effort. Collaborate with development teams to identify and resolve quality issues early in the product lifecycle. Conduct thorough testing across various environments, including local, staging, and production, to ensure seamless deployment of products. Participate in code reviews and provide feedback on testability and maintainability of codebases. Who We're Looking For We are seeking a highly skilled Lead Quality Assurance Engineer with experience in machine learning environments. You should have a deep understanding of testing methodologies, strong technical skills, and the ability to work effectively in a fast-paced environment. A background in sports analytics or similar fields is a plus. 5+ years of experience as a QA engineer, preferably in a machine learning context. Demonstrated expertise in automated testing frameworks and tools. Strong understanding of software development lifecycle (SDLC). Experience with test-driven development (TDD) and behavior-driven development (BDD). Affinity for sports or experience working in the sports industry is a bonus. Working at Hudl At Hudl, we value our employees and provide a supportive work environment that fosters growth and innovation. Our team has been recognized as one of Newsweek's Top 100 Global Most Loved Workplaces in 2023. We believe in the power of sports to inspire teamwork and dedication, and we are committed to helping teams around the world see their game differently. Join us and be part of a team that is dedicated to making a positive impact through technology and innovation. Apply Today To apply, complete your application directly on this…
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