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Applied Scientist - AI/ML Engineer

EPAM Systems

remote globalPosted Jul 13, 2026
Posting intelligenceActively listedReposted 6×, possible evergreen/ghost posting

Skills

classificationpythonawsml

About the role

We are seeking an Applied Scientist - AI/ML Engineer to maximize the potential of large language models through advanced prompt engineering and a deep understanding of video workflows.

In this role, you will heavily iterate on Amazon Bedrock models to optimize outcomes by refining prompts that detect sports moments using transcripts and video frames within a multi-modal framework. You will process test video assets through Amazon Bedrock for custom moments detection, configure and optimize models to maximize accuracy, and build repeatable templates for pipeline processing and structured metadata output.

Responsibilities

Design and optimize prompts for multimodal foundation models (Claude, Nova, etc.) to detect custom ad moments in live video frames and audio transcripts

Conduct model comparison studies with accuracy benchmarking on domain-specific content

Configure and tune the Bedrock Connector pipeline for each custom moment type

Validate detection accuracy across multiple sports, genres, and live event types

Fine-tune prompts iteratively to improve detection accuracy and outcomes

Collaborate with the AWS Elemental Inference team to align on technical direction

Develop Python scripts to automate custom moments pipelines when needed

Build repeatable templates for pipeline processing and structured metadata output

Requirements

3+ years of experience in applied AI/ML with a background in multimodal models (vision + language)

Hands-on expertise in prompt engineering for large foundation models, preferably using Amazon Bedrock

Proficiency in Python for scripting and pipeline automation

Familiarity with video/image understanding in live video workflows and near-real-time inference pipelines

Ability to design evaluation frameworks and benchmark model accuracy

Experience working in media, advertising, or content classification

Understanding of Media Supply Chain concepts and workflows

Proficiency in English at an Upper-Intermediate level (B2) or higher

Nice to have

Familiarity with working with video frames using OpenCV and transcript data

Knowledge of computer vision and natural language processing techniques

Prior experience in sports analytics or media technology

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

Award-winning culture recognized by Glassdoor, Newsweek and LinkedIn

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