Senior ML Ops Engineer: GenAI & RAG Pipelines

Elsevier; City Of London; On-site; GBP 70,000 - 117,000; Full time

Job summary

Elsevier, a leading global information analytics company, is seeking a Senior Machine Learning Engineer to bridge data science and engineering for secure, scalable AI-driven workflows. You will work on AI-based features, knowledge-graph retrieval, and content confidentiality across Health platforms like Clinical Key AI and Sherpath AI.

You will design and optimize ML pipelines, deploy MLOps solutions, and collaborate with product managers, data scientists, and Responsible AI teams.

Qualifications

• Proficient in ML engineering and MLOps with production experience.
• Experience shipping ML or search/GenAI systems to production.
• Hands-on with cloud platforms (AWS, Azure, GCP).
• Familiarity with vector/search/graph tech and LLM eval.
• Knowledge of data science life cycle: feature engineering, training, evaluation.

Responsibilities

• Automate and orchestrate ML workflows across major cloud platforms.
• Maintain model registries and artifacts for reproducibility and governance.
• Develop CI/CD pipelines for ML including data validation and testing.
• Implement ML engineering solutions using ML platforms (SageMaker, MLflow, Azure ML).
• Design GAR+RAG components and prompt libraries with guardrails for LLMs.

Skills

Python

Java/Scala

Cloud platforms

ML/Ops

Tools

Elasticsearch/OpenSearch/Solr

Neo4j

MLflow

SageMaker

Azure ML

Job description

Elsevier, a leading global information analytics company, is seeking a Senior Machine Learning Engineer to bridge data science and engineering for secure, scalable AI-driven workflows. You will work on AI-based features, knowledge-graph retrieval, and content confidentiality across Health platforms like Clinical Key AI and Sherpath AI.

You will design and optimize ML pipelines, deploy MLOps solutions, and collaborate with product managers, data scientists, and Responsible AI teams.