Jobs at Elsevier

Design, build, evaluate, and scale production-ready AI solutions (LLMs, NLP, retrieval, and generative AI) to support scientific discovery. Develop RAG systems, semantic search, summarization, QA, ranking, recommendation, and evaluation frameworks. Integrate knowledge graphs and domain metadata, partner with engineering and product teams, lead technical decisions, and mentor data scientists.

Design, develop, and deploy ML, NLP, and generative-AI solutions (including LLMs and RAG) to improve search, retrieval, recommendation, and question-answering across scientific publications and datasets. Build scalable pipelines, evaluation frameworks, and production-quality Python code while collaborating with engineering, product, UX, and domain experts to measure and improve model reliability, relevance, and user impact.

Lead the design and delivery of scalable search and retrieval systems, guide a team of engineers, and own technical outcomes for a shared search platform. Build services and data workflows (Elasticsearch, Spark, Airflow), write production Python/Java code, integrate vector/semantic search and LLM/GenAI features, mentor engineers, and ensure observability, performance, and cross-team alignment.

Lead and develop high-performing data science teams to build AI-powered search, retrieval, NLP, generative AI, and knowledge systems for scientific discovery. Define strategy, drive production deployments, establish evaluation and responsible AI practices, partner with product and engineering, mentor staff, and influence senior stakeholders to deliver measurable impact.

As a Senior ML Ops Engineer, you will bridge Data Science and Engineering to automate ML workflows, manage CI/CD for ML systems, and collaborate with various teams to implement solutions for AI features and services.

The Senior Site Reliability Engineer will manage and optimize cloud infrastructure on AWS, design Kubernetes clusters, and automate workflows while mentoring junior members.

Lead go-to-market strategy, positioning, and messaging for Elsevier's Academic Leaders and Funders portfolio. Translate technical AI and data capabilities into compelling narratives, drive coordinated product launches, enable sales with materials and training, and perform competitive and market analysis to increase adoption, deal velocity, and revenue.

Lead enablement, tooling, and operational excellence for Clinical Solutions product management. Build training, playbooks, and governance for roadmap tools; track PM health metrics; coordinate leadership forums; drive cross‑functional alignment and continuous improvement of processes and tooling.

Lead design and implementation of large-scale search and retrieval systems, improve relevance using lexical and vector techniques, build scalable data workflows and microservices (Spark, Airflow), write testable code in Python/Java/Scala, diagnose distributed system issues, mentor engineers, and collaborate across product and platform teams to deliver production search infrastructure.

The Account Manager will drive sales and renewals, manage customer relationships, and support customers with diverse needs while achieving bookings and conducting market evaluations.