Senior MLOps Engineer

Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global organization?

Are you looking to drive cutting edge products that have a true societal impact?

About the team, this team that powers Elsevier’s Health platforms: Clinical Key AI, Sherpath AI, and AI-driven automated clinical and content workflows. You will bridge Data Science and Engineering to turn experimental NLP/IR/GenAI models into secure, reliable, and scalable services. Our systems operate over one of the world’s largest medical and scholarly landscapes.

About the role, as a Senior Machine Learning Engineer you’ll work on AI-based features (GenAI, Agentic AI, RAG, etc.) search/ranking quality, and knowledge graph aware retrieval while enforcing content rights and editorial confidentiality.

Key Responsibilities

ML & LLM Engineering, Search and Recommendation Engines

• Automate and orchestrate machine learning workflows across major cloud and AI platforms (AWS, Azure, Databricks, and foundation model APIs such as OpenAI). • Maintain and version model registries and artifact stores to ensure reproducibility and governance. • Develop and manage CI/CD for ML, including automated data validation, model testing, and deployment. • Implement ML Engineering solutions using popular MLOps platforms such as AWS SageMaker, MLflow, Azure ML. • Scale end-end custom Sagemaker pipelines. • Design and implement the engineering components of GAR+RAG systems (e.g., query interpretation…