Senior MLOps Engineer

About the role

Elsevier is looking for a Senior MLOps Engineer to join its team that powers research platforms such as Scopus, ScienceDirect and journal submission and peer review workflows. The role bridges Data Science and Engineering, turning experimental NLP, IR and GenAI models into secure, reliable and scalable services. It is a hybrid position in Mexico City (Reforma) with flexible hours.

Key responsibilities

• Automate and orchestrate ML workflows across AWS, Azure, Databricks and foundation model APIs such as OpenAI
• Maintain model registries and artifact stores, and build CI/CD for ML with data validation, model testing and deployment
• Implement MLOps solutions with AWS SageMaker, MLflow and Azure ML, including custom SageMaker pipelines for recommendation systems
• Design GAR+RAG systems (query interpretation, chunking, embeddings, hybrid retrieval, semantic search) and manage prompt libraries, guardrails and structured output for LLMs on Bedrock/SageMaker or self-hosted
• Build ML pipelines using Elasticsearch/OpenSearch/Solr, vector DBs and graph DBs
• Build evaluation pipelines with offline IR metrics (NDCG, MAP, MRR), LLM quality metrics (faithfulness, grounding) and A/B testing
• Optimize infrastructure costs through monitoring, scaling and efficient resource use, and stay current with GenAI, NLP and RAG research
• Partner with SMEs, Product Managers, Data Scientists and Responsible AI experts, and work with Operations Engineers

Required profile

• 3-5+ years in ML engineering, MLOps platforms and shipping ML or search/GenAI systems to production
• Strong Python, Java and/or Scala engineering
• Experience with statistical analysis, ML theory and NLP
• Hands-on experience with AWS, Azure and/or Google Cloud
• Experience evaluating LLM models and background in scholarly publishing workflows, bibliometrics or citation graphs

Required skills

• Search/vector/graph technologies such as Elasticsearch/OpenSearch/Solr and Neo4j
• Familiarity with PyTorch, TensorFlow and PySpark
• Understanding of the Data Science Life Cycle and large-scale data processing systems

What we offer

• Private medical, dental and vision plan, savings fund with company matching, life insurance and grocery voucher
• Vacation bonus, minor medical expenses discount card and Employee Assistance Programme
• Learning and development resources, awards and time off for charity
• Flexible hybrid work in Mexico City with flexible hours