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 supports Elsevier’s large-scale research platforms by turning experimental NLP, search, and GenAI models into secure, reliable, and scalable production services.
We promote a healthy work/life balance and offer comprehensive benefits including pension plans, flexible working hours, and various leave options.
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
ML pipelines and MLOps infrastructure
Cloud platforms AWS Azure Databricks
Search vector graph technologies
Python Java Scala programming
CI/CD for ML models
Evaluation pipelines with IR and LLM metrics
Nice-to-have
Collaboration with product and domain experts
Flexible working hours and wellbeing initiatives
Experience with scholarly publishing workflows
Knowledge of generative AI and RAG systems
Key Requirements
5+ years ML Engineering and MLOps experience
Strong Python Java Scala skills
Experience with AWS Azure or Google Cloud
Experience shipping ML or GenAI systems to production
Familiarity with ML frameworks PyTorch TensorFlow PySpark
Experience in large scale data processing systems like Spark
Background in scholarly publishing or bibliometrics