You will bridge Data Science and Engineering to turn experimental NLP/IR/GenAI models into secure, reliable, and scalable services
Job Summary
You will bridge Data Science and Engineering to turn experimental NLP/IR/GenAI models into secure, reliable, and scalable services.
This role involves automating and orchestrating machine learning workflows across major cloud and AI platforms while maintaining model registries and artifact stores.
Elsevier offers a mission-driven global environment with competitive base pay ranges and country-specific benefits, committed to an accessible and fair hiring process.
Matching Summary
You will bridge Data Science and Engineering to turn experimental NLP/IR/GenAI models into secure, reliable, and scalable services.
Salary
Base: $95,300 - $158,800; Bonus/Equity: Eligible for annual incentive bonus; Benefits: Country specific benefits available
Skills & Requirements
Must-have
ML Engineering and MLOps platforms
Cloud platforms AWS Azure Databricks
Search vector graph technologies
CI/CD for ML pipelines
LLM model evaluation
Python programming
Nice-to-have
Health technology and medical content workflows
Collaboration with cross-functional teams
Experience with PyTorch TensorFlow PySpark
Knowledge of natural language processing
Experience with large-scale data processing
Key Requirements
Current experience shipping ML or GenAI systems to production
Strong Python Java or Scala experience
Hands-on experience with AWS Azure or Google Cloud
Experience with Elasticsearch OpenSearch Solr Neo4j