We are seeking an Applied Scientist to join our team, focused on leveraging existing AI/ML models to detect key moments in sports videos through computer vision and transcript analysis. This role emphasizes prompt engineering, model output validation and integration with inference pipelines rather than custom model development or training.
Responsibilities
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Design and optimize prompts for multimodal foundation models such as Claude and Nova to detect custom ad moments in live video frames and audio transcripts
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Process test video assets through Amazon Bedrock for custom moments detection using transcript analysis and computer vision
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Configure and tune the Bedrock Connector pipeline for each custom moment type
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Conduct model comparison studies with accuracy benchmarking on specific content
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Validate detection accuracy across multiple sports, genres and live event types and refine prompts to improve accuracy
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Build repeatable templates for pipeline processing and structured metadata output
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Collaborate with the AWS Elemental Inference team to align on integration requirements
Requirements
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5+ years of experience in applied AI/ML with a focus on multimodal models spanning vision and language
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Expertise in prompt engineering for large foundation models, with Amazon Bedrock preferred
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Familiarity with video/image understanding in live video workflows and near-real-time inference pipelines
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Skills in designing evaluation frameworks and benchmarking model accuracy
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Experience working in media, advertising or content classification
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English proficiency at B2 level or higher
Nice to have
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Familiarity with video frames using OpenCV and transcript data for understanding input data
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Knowledge of computer vision and natural language processing techniques
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Background in sports analytics or media technology
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.
