3 дня назад
Data Scientist AI (GenAI)
Мэтч & Сопровод
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Описание вакансии
Текст:
TL;DR
Data Scientist AI (GenAI) (LLM/RAG): Improving an in-house chatbot through context engineering, retrieval, evaluation, and structured experimentation with an accent on diagnosing chatbot behaviour and grounding responses. Focus on building evaluation frameworks, improving context ingestion and retrieval, and translating user and stakeholder feedback into technical improvements.
Location: Utrecht, Netherlands; must be located in the Netherlands
Company
is recruiting for a large organisation in the Dutch financial sector developing an in-house chatbot.
What you will do
- Analyse chatbot outputs and identify high-impact improvements.
- Diagnose context gaps, grounding issues, data-flow problems, and context-ingestion failures.
- Define agent-performance evaluation criteria with product owners and engineers.
- Work with use-case teams and stakeholders to incorporate real-world scenarios and feedback into evaluations.
- Improve retrieval, data structuring, and onboarding of new context sources.
- Build evaluation frameworks for fast, large-scale experimentation and translate functional requirements into technical improvements.
Requirements
- Hands-on experience with LLM-based applications and retrieval-augmented generation.
- Strong understanding of prompts, context windows, retrieval, grounding, and chatbot output quality.
- Experience with API integrations, batch synchronisation, and structured and unstructured data.
- Ability to debug data flows and context-ingestion issues with engineers.
- Experience designing evaluation approaches beyond classical machine-learning metrics.
- Strong functional understanding of chatbot use cases, user behaviour, and collaboration between engineering, product, and stakeholders.
Nice to have
- Experience with human-in-the-loop evaluation.
Culture & Benefits
- Contract-to-permanent opportunity with a possible transition to an internal position.
- Initial project duration of 12 months.
- 36-hour working week.
- Focus on curiosity, structured thinking, practical debugging, and improving AI-system behaviour.
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