Retrieval-augmented generation (rag) system design
Python programming with pytorch and hugging face
Elsevier’s mission is to help researchers, clinicians, and life sciences professionals advance discovery and improve health outcomes through trusted content, data, and analytics
Job Summary
Elsevier’s mission is to help researchers, clinicians, and life sciences professionals advance discovery and improve health outcomes through trusted content, data, and analytics.
This role will lead a team advancing lexical, vector, and hybrid retrieval systems and designing robust evaluation frameworks to power discovery experiences for millions of users.
The company promotes a healthy work/life balance with flexible working hours, comprehensive benefits, and a culture of innovation, collaboration, and excellence.
Matching Summary
Elsevier’s mission is to help researchers, clinicians, and life sciences professionals advance discovery and improve health outcomes through trusted content, data, and analytics.
Skills & Requirements
Must-have
lexical search and vector retrieval expertise
retrieval-augmented generation (RAG) system design
Python programming with PyTorch and Hugging Face
building scalable evaluation frameworks
leading data science teams
enterprise-scale AI and retrieval innovation
Nice-to-have
deploying retrieval-enhanced LLMs in production
familiarity with scientific ontologies and metadata standards
strong communication and stakeholder management
experience in academic publishing or research intelligence
Key Requirements
PhD or MSc in Computer Science or related field
6+ years experience in search or retrieval systems