Senior Data Scientist

Jobtailor; Amsterdam; On-site; EUR 70,000 - 110,000; Full time

Job summary

Jobtailor is seeking a researcher to lead the development and evaluation of advanced search and generative AI systems in a production environment. You will own complex problems end-to-end, drive rigorous evaluation, and steer the technical direction of retrieval and RAG systems.

You will design and optimize lexical, vector, and hybrid retrieval at scale, architect RAG pipelines, and collaborate with engineering to deliver robust, production-ready implementations.

Qualifications

• Master’s or PhD in Computer Science, Data Science, ML or related field, or equivalent practical experience.
• 3–5+ years of experience in data science, ML, or applied NLP.
• Hands-on with search/retrieval systems (lexical, vector, hybrid).
• Experience with RAG pipelines and LLM-based systems.
• Knowledge of evaluation methods for ML/IR/GenAI, and solid Python skills.

Responsibilities

• Lead development and evaluation of advanced search and generative AI systems.
• Own complex problem areas end-to-end and drive rigorous evaluation.
• Design and optimize lexical, vector, and hybrid retrieval at scale.
• Architect and improve RAG pipelines, including prompts and orchestration.
• Experiment with embeddings, re-ranking models, and retrieval architectures.
• Collaborate with engineering for production-ready implementations.
• Define evaluation strategies for search and GenAI across products.
• Contribute to responsible AI practices including bias and risk evaluation.
• Collaborate with domain experts to integrate scientific taxonomies and ontologies.
• Take ownership from problem definition through deployment.

Skills

Search systems

RAG pipelines

LLM-based systems

Evaluation methodologies

Python

PyTorch

Hugging Face

LangChain

LangGraph

Haystack

Databricks

Experiment design

Statistical analysis

Education

Master’s or PhD in Computer Science, Data Science, Machine Learning

Tools

PyTorch

Hugging Face

LangChain

LangGraph

Haystack

Databricks

Job description

Responsibilities

• Lead the development and evaluation of advanced search and generative AI systems
• Own complex problem areas end-to-end, drive methodological rigor in evaluation, and contribute to the technical direction of retrieval and RAG systems
• Play a leading role in the design and optimization of lexical, vector, and hybrid retrieval systems at scale
• Help architect and improve RAG pipelines, including retrieval strategies, prompt design, and system orchestration (e.g., LangGraph-based workflows)
• Drive experimentation with embeddings, re-ranking models, and retrieval architectures to significantly improve relevance and user outcomes
• Partner with engineering to ensure robust, scalable, and production-ready implementations
• Help define and evolve evaluation strategies for search and generative AI systems across products
• Contribute to responsible AI practices, including bias, fairness, and risk evaluation
• Collaborate with domain experts, ontology engineers, and biomedical informaticians to integrate scientific taxonomies, citation networks, and clinical ontologies into retrieval systems
• Take ownership of projects from problem definition through experimentation and deployment

Requirements

• Master’s or PhD in Computer Science, Data Science, Machine Learning, or a related field (or equivalent practical experience)
• ~3–5+ years of experience in data science, machine learning, or applied NLP
• Strong hands-on experience with:
  • Search and retrieval systems (lexical, vector, hybrid)
  • RAG pipelines and LLM-based systems
  • Evaluation methodologies for ML / IR / GenAI
  • Advanced programming skills in Python
  • Experience with modern ML/NLP frameworks (e.g., PyTorch, Hugging Face, LangChain, LangGraph, Haystack)
  • Experience working with Databricks or similar distributed data/ML platforms
  • Strong understanding of experimentation design and statistical analysis