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# Associate Principal - Data Sciences

- **Company:** LTM Inc
- **Location:** Tampa, FL, United States
- **Salary:** $105,430.0 - $173,000.0
- **Contract:** Internship / Graduate position
- **Skills:** Artificial Intelligence, Amazon Web Services, Amazon S3, Data Analysis, JSON, Python (Programming Language), Cloud Services, Delivery Pipeline, Large Language Models, Prompt Engineering, Generative AI, Data Pipelines, Automation Anywhere, Serverless Computing
- **Published:** June 24, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=b769a1cf2ba8dc4e

## About the Role

Do you have experience in Serverless cloud services?, Strong experience in

Prompt engineering for foundation models Claude Nova etc

Multimodal AI systems vision NLP

Handson experience with

LLM inference and optimisation

Structured outputs JSON generation and validation Strong Python programming and data pipeline skills

Familiarity with AWS cloud stackBedrock Lambda S3 analytics pipeline

Experience in working withVideo analytics media AI workflows Realtime or near realtime systems
Skills

Mandatory Skills : AI/Generative AI, AWS Bedrock
Other details

## Description

Role OverviewWe are hiring Applied Scientists to design build and optimise GenAIdriven multimodal pipelines for detecting contextual moments in live video streams

This role focuses on prompt engineering multimodal inference and model optimisation using foundation models Claude Nova Bedrock to maximise detection accuracyKey Responsibilities

Design and optimise prompt engineering strategies for foundation models

Build pipelines for multimodal inference video transcript audio

Detect and classify custom moments and contextual events

Develop reusable frameworks for

Moment detection templates

Structured metadata generation

Finetune prompts and configurations to improve

Accuracy

Precision across moment types

Integrate GenAI outputs into

Structured JSON metadata

Downstream systems and pipelines

Work with AWS services such as

Amazon Bedrock GenAI models

Lambda S3 Kinesis data pipeline

Collaborate with QA team for output validation and optimisation

Support production rollout and continuous improvement


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