We are seeking a Senior QA Engineer to validate the performance of AI-driven video analysis systems, with a focus on detecting key moments in sports content. The role combines manual and automation testing, working with pre-labeled video assets provided by the customer.
Responsibilities
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Audit live sports events across leagues such as NBA, MLB, NFL, and NHL to confirm that the AI/Inference Service accurately tracks and labels major sports moments, including touchdowns, home runs, and buzzer-beaters, exactly as they occur
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Apply strong knowledge of sports contexts, terminology, and metrics while working with timecodes, video frames, transcriptions, and captions
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Act as the human expert who identifies when the AI produces errors, hallucinations, or misinterprets a sports rule, partnering directly with AWS engineers to document defects and validate their resolutions
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Review and validate metadata tags generated by the AI to ensure they align with the sport being analyzed and meet advertising industry standards (IAB rules), keeping content brand-safe for ad placements
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Maintain detailed QC documentation, keeping clear records of AI and Inference Service performance, tracking accuracy metrics, and helping establish a smooth testing process that connects traditional sports broadcasting with emerging AI technology
Requirements
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At least 3 years of professional relevant experience in QA engineering
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Experience in both manual and automation QA, preferably within video-focused or AI-driven environments
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Knowledge of testing Large Language Models (LLMs) along with an understanding of the associated workflows
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Automation scripting skills using languages and tools such as Python, Selenium, or similar for comparing JSON outputs to ground truth at scale
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Solid understanding of software development and QA cycles, including defect logging, triage, and reporting
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Ability to interpret labeled data and validate model outputs against expected results
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Familiarity with concepts such as computer vision and transcript analysis, without the need to understand internal model workings
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Strong communication skills for stakeholder interaction and reporting
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Detail-oriented and iterative approach to testing activities
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Fluent English communication skills at a B2 level or higher, both written and verbal
Nice to have
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Hands-on experience with video testing tools or frameworks dedicated to media QA
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Prior work in sports analytics or media technology environments
We offer
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International projects with top brands
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Work with global teams of highly skilled, diverse peers
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Healthcare benefits
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Employee financial programs
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Paid time off and sick leave
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Upskilling, reskilling and certification courses
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Unlimited access to the LinkedIn Learning library and 22,000+ courses
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Global career opportunities
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Volunteer and community involvement opportunities
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EPAM Employee Groups
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Award-winning culture recognized by Glassdoor, Newsweek and LinkedIn
EPAM is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, sexual orientation, gender identity or expression, disability, protected veteran status, or any other characteristic protected by applicable law.
