Senior MLOps Engineer

About the team

Elsevier’s mission is to help researchers, clinicians, and life sciences professionals advance discovery and improve health outcomes through trusted content, data, and analytics. As the landscape of science and healthcare evolves, we are pioneering intelligent discovery experiences—from Scopus AI and Leap Space to Clinical Key AI, Pharma Pendium, and next‑generation life sciences platforms. These products leverage retrieval‑augmented generation (RAG), semantic search, and generative AI to make knowledge more discoverable, connected, and actionable across disciplines.

This role supports Elsevier’s large‑scale research platforms by turning experimental NLP, search, and GenAI models into secure, reliable, and scalable production services. It focuses on ML and LLM engineering across cloud platforms, including building end‑to‑end ML pipelines, MLOps infrastructure, and CI/CD for models used in search, recommendations, and RAG‑based systems. The position involves designing and operating retrieval, ranking, and evaluation pipelines, including IR metrics, LLM quality metrics, and A/B testing, while optimizing cost and performance  will collaborate closely with product managers, domain experts, data scientists, and operations engineers to deliver high‑quality, responsible AI features over a massive scholarly corpus.

The role suits an experienced ML engineer with strong cloud, search, and NLP expertise who wants to work at the intersection of GenAI, research content, and production‑grade systems.

• 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 Sage Maker, MLflow, and Azure ML.
• End‑to‑end custom Sage Maker pipelines for recommendation systems.
• Design and implement the engineering components of GAR+RAG systems (e.g., query interpretation, reflection, chunking, embeddings, hybrid retrieval, semantic search); manage prompt libraries, guardrails, and structured output for LLMs hosted on Bedrock/Sage Maker or self‑hosted.
• Design and implement ML pipelines that utilize Elasticsearch, Open Search, Solr, vector DBs, and graph DBs.
• Build evaluation pipelines: offline IR metrics (e.g., NDCG, MAP, MRR), LLM quality metrics (e.g., faithfulness, grounding), and A/B testing.
• Optimize infrastructure costs through monitoring, scaling strategies, and efficient resource utilization.
• Stay current with the latest GAI research, NLP and RAG and apply the state‑of‑the‑art in our experiments and systems.

• Partner with subject‑matter experts, product managers, data scientists, and responsible AI experts to translate business problems into cutting‑edge data science solutions.
• Collaborate and interface with operations engineers who deploy and run production infrastructure.

• 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, machine learning theory, and natural language processing.
• Hands‑on experience with major cloud vendor solutions (AWS, Azure, and/or Google).
• Experience with search, vector, and graph technologies (e.g., Elasticsearch, Open Search, Solr, Neo4j).
• Experience evaluating LLM models.
• Background with scholarly publishing workflows, bibliometrics, or citation graphs.
• A strong understanding of the data science life cycle, including feature engineering, model training, and evaluation metrics.
• Familiarity with ML frameworks, e.g., PyTorch, Tensor Flow, and PySpark.
• Experience with large‑scale data processing systems, e.g., Spark.

Join our team and contribute to a culture of innovation, collaboration, and excellence. If you are ready to advance your career and make a significant impact, we encourage you to apply.

We are an equal‑opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law.

If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or contact 1‑855‑833‑5120.