Role 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
Required Skills Experience
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
