This role supports Elsevier's large-scale research platforms by turning experimental NLP, search, and GenAI models into secure, reliable, and scalable production services
Job Summary
This role supports Elsevier's large-scale research platforms by turning experimental NLP, search, and GenAI models into secure, reliable, and scalable production services.
The position involves designing and operating retrieval, ranking, and evaluation pipelines while optimizing cost and performance at scale across massive scholarly corpora.
Join a team that promotes a healthy work/life balance with flexible working hours, sabbaticals, and comprehensive benefits including study assistance.
Matching Summary
This role supports Elsevier's large-scale research platforms by turning experimental NLP, search, and GenAI models into secure, reliable, and scalable production services.
Skills & Requirements
Must-have
5+ years ML Engineering experience
Python Java Scala engineering skills
AWS Azure Google Cloud platform expertise
Elasticsearch OpenSearch Solr vector DBs
LLM evaluation and A/B testing pipelines
Nice-to-have
Scholarly publishing workflow knowledge
Bibliometrics or citation graph experience
Strong understanding of Data Science Life Cycle
Experience with PyTorch TensorFlow PySpark
Familiarity with large scale Spark data processing