Senior QA Engineer

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

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

Apply strong knowledge of sports contexts, terminology, and metrics while working with timecodes, video frames, transcriptions, and captions

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

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

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

At least 3 years of professional relevant experience in QA engineering

Experience in both manual and automation QA, preferably within video-focused or AI-driven environments

Knowledge of testing Large Language Models (LLMs) along with an understanding of the associated workflows

Automation scripting skills using languages and tools such as Python, Selenium, or similar for comparing JSON outputs to ground truth at scale

Solid understanding of software development and QA cycles, including defect logging, triage, and reporting

Ability to interpret labeled data and validate model outputs against expected results

Familiarity with concepts such as computer vision and transcript analysis, without the need to understand internal model workings

Strong communication skills for stakeholder interaction and reporting

Detail-oriented and iterative approach to testing activities

Fluent English communication skills at a B2 level or higher, both written and verbal

Nice to have

Hands-on experience with video testing tools or frameworks dedicated to media QA

Prior work in sports analytics or media technology environments

We offer

International projects with top brands

Work with global teams of highly skilled, diverse peers

Healthcare benefits

Employee financial programs

Paid time off and sick leave

Upskilling, reskilling and certification courses

Unlimited access to the LinkedIn Learning library and 22,000+ courses

Global career opportunities

Volunteer and community involvement opportunities

EPAM Employee Groups

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