Senior Threat Researcher investigating AI - enabled cybercrime for Flare, a cybersecurity SaaS company. Presenting threat intelligence and advising customers, ISACs, and executives on autonomous attacks.
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Applied Data Scientist
Posted via LinkedIn Recruiter (not a company profile)
Posted 2 weeks ago
About the role
- Hiring Applied Scientists to build GenAI multi-modal pipelines for live video moment detection, focusing on prompt engineering and model optimization.
Responsibilities
- We are hiring Applied Scientists (1 Lead + 2 ICs) to design, build, and optimise GenAI-driven multi-modal 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 accuracy. Key Responsibilities: Design and optimise prompt engineering strategies for foundation models. Build pipelines for multi-modal inference (video + transcript + audio). Detect and classify custom moments and contextual events Develop reusable frameworks for Moment detection templates Structured metadata generation, Fine-tune 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.
Requirements
- Strong experience in: Prompt engineering for foundation models (Claude, Nova, etc.). Multi-modal AI systems (vision + NLP). Hands-on experience with LLM inference and optimisation. Structured outputs (JSON generation and validation) Strong Python programming and data pipeline skills. Familiarity with AWS cloud stack: Bedrock, Lambda, S3, analytics pipeline. Experience in working with: Video analytics / media AI workflows Real-time or near real-time systems
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