Staff Applied Scientist

Markteinblicke

Stack

Details

Kostenlos, nach der Anmeldung.

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Beschreibung

Accountabilities: - Knowledge Graph Development: Design, build, and maintain production-grade knowledge graphs that transform unstructured content into structured, reliable, and accessible knowledge. Lead ontology design, information extraction, and entity resolution to improve data quality and usability. - AI Agents and Intelligent Retrieval: Develop and deploy LLM-powered agents and agentic retrieval systems capable of finding, validating, and using relevant information. Implement planning, tool integration, and orchestration mechanisms to deliver dependable, context-aware results. - Model Evaluation and Continuous Improvement: Establish robust evaluation frameworks and quality metrics to measure model performance and determine production readiness. Incorporate real-world user feedback to improve knowledge accuracy, retrieval relevance, and overall system effectiveness. - Applied Machine Learning and NLP: Apply advanced machine learning, natural language processing, retrieval-augmented generation (RAG), and LLM fine-tuning techniques to solve complex product challenges. Combine modern language models with classical machine learning approaches to improve reliability and performance. - Technical Strategy and Architecture: Set technical direction for applied science initiatives, evaluate emerging technologies, and make informed build-versus-buy decisions. Establish scalable approaches to experimentation, model deployment, and production engineering. - Cross-Functional Product

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