This role will lead a group of applied scientists advancing lexical, vector, and hybrid retrieval systems; designing robust evaluation frameworks; and shaping the foundation of Elsevier’s next-generation search and AI ecosystem
Job Summary
This role will lead a group of applied scientists advancing lexical, vector, and hybrid retrieval systems; designing robust evaluation frameworks; and shaping the foundation of Elsevier’s next-generation search and AI ecosystem.
Define and own the evaluation framework for retrieval and generative AI systems, combining traditional IR metrics with GenAI-specific measures such as factual consistency and hallucination rates.
We promote a healthy work/life balance across the organisation. We offer an appealing working prospect for our people.
Matching Summary
This role will lead a group of applied scientists advancing lexical, vector, and hybrid retrieval systems; designing robust evaluation frameworks; and shaping the foundation of Elsevier’s next-generation search and AI ecosystem.
Skills & Requirements
Must-have
Search and retrieval systems
Vector retrieval and RAG
Evaluation frameworks for AI
Python programming proficiency
Leadership and team mentoring
Nice-to-have
Responsible AI standards
Human-in-the-loop quality ratings
Scientific ontologies and metadata
Flexible working hours
Culture of innovation and collaboration
Key Requirements
PhD or MSc in relevant field
6+ years of experience
2+ years in leadership role
Experience with PyTorch, Hugging Face, LangGraph or Haystack