Senior MLOps Engineer for GenAI & Search Systems

Elsevier; Amsterdam; On-site; EUR 110,000 - 140,000; Full time

Benefits offered by this job

Wellbeing initiatives

Shared parental leave

Study assistance

Sabbaticals

Job summary

Elsevier is seeking an experienced ML Engineer/ML Ops expert to bridge Data Science and Engineering for GenAI-based features and secure, scalable services. You will participate in search/ranking quality, RAG, and knowledge-graph aware retrieval within Life Sciences applications.

You will collaborate with Data Scientists, Engineers and Product Managers to translate business problems into cutting-edge data science solutions, while ensuring content rights and confidentiality across enterprise

Qualifications

• 5+ years in ML engineering or shipping ML / GenAI systems to production.
• Experience with statistics, ML theory and NLP.
• Hands-on with AWS, Azure and/or Google cloud platforms.
• Knowledge of search/vector/graph tech (Elasticsearch/OpenSearch/Solr, Neo4j).
• Experience evaluating LLM models and data-centric ML workflows.

Responsibilities

• Automate and orchestrate ML workflows across cloud platforms.
• Maintain model registries and artifact stores for reproducibility.
• Develop and manage CI/CD for ML, with data validation and testing.
• Implement ML engineering using Sagemaker, MLflow, Azure ML.
• Design GAR+RAG systems; manage prompts and guardrails for LLMs.
• Design ML pipelines with vector DBs, ES/OpenSearch, graph DBs; evaluate IR metrics.

Skills

ML Engineering

MLOps

NLP

Cloud platforms

Model deployment

Tools

PyTorch

TensorFlow

PySpark

Elasticsearch/OpenSearch/Solr

Neo4j / Graph DBs

Job description

Elsevier is seeking an experienced ML Engineer/ML Ops expert to bridge Data Science and Engineering for GenAI-based features and secure, scalable services. You will participate in search/ranking quality, RAG, and knowledge-graph aware retrieval within Life Sciences applications.

You will collaborate with Data Scientists, Engineers and Product Managers to translate business problems into cutting-edge data science solutions, while ensuring content rights and confidentiality across enterprise