Are you passionate about building scalable AI and machine learning systems that power world-leading research and healthcare platforms? Do you enjoy turning cutting-edge NLP, search, recommendation, and Generative AI innovations into reliable, secure, and production-ready solutions that create real-world impact? About our Team Our global team support products education electronic health records that introduce students to digital charting and prepare them to document care in today’s modern clinical environment. We have a very stable product that we’ve worked to get to and strive to maintain. Our team values trust, respect, collaboration, agility, and quality. About the Role Join the team that powers Elsevier’s research platforms—Scopus/Scopus AI, ScienceDirect/ScienceDirect AI, and journal submission & peer review workflows. You will bridge Data Science and Engineering to turn experimental NLP/IR/GenAI models into secure, reliable, and scalable services. Our systems operate over one of the world’s largest scholarly corpora, so you’ll work on AI-based features (GenAI, Agentic AI, RAG, etc.) search/ranking quality, and knowledge graph aware retrieval while enforcing content rights and editorial confidentiality. Key Responsibilities ML & LLM Engineering, Search and Recommendation Engines 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 SageMaker, MLflow, Azure ML. End-to-end custom SageMaker pipelines for recommendation systems. Design and implement the engineering components of GAR+RAG systems (e.g., query interpretation and reflection, chunking, embeddings, hybrid retrieval, semantic search), manage prompt libraries, guardrails and structured output for LLMs hosted on Bedrock/SageMaker or self-hosted Design and implement ML pipelines that utilize Elasticsearch/OpenSearch/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 Collaboration 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. Required Qualifications 3–5+ years in ML Engineering, MLOps platforms, 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) Search/vector/graph technologies (e.g., Elasticsearch / OpenSearch / Solr/ Neo4j). Experience in 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, TensorFlow, PySpark Experience with large scale data processing systems, e.g., Spark Work in a Way That Works for You We promote a healthy work/life balance across the organisation. We offer an appealing working prospect for our people. With numerous wellbeing initiatives, shared parental leave, study assistance, and sabbaticals, we will help you meet your immediate responsibilities and your long-term goals. Working Pattern Working flexible hours - flexing the times when you work in the day to help you fit everything in and work when you are the most productive. About the Business A global leader in information and analytics, we help researchers and healthcare professionals advance science and improve health outcomes for the benefit of society. Building on our publishing heritage, we combine quality information and vast data sets with analytics to support visionary science and research, health education and interactive learning, as well as exceptional healthcare and clinical practice. At Elsevier, your work contributes to the world's grand challenges and a more sustainable future. We harness innovative technologies to support science and healthcare to partner for a better world. Primary Location Base Pay Range: NLD Amsterdam (Radarweg) €53,800 - €89,900. This role is covered by the Collective Labor Agreement Publishing Industry. We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location. We are committed to providing a fair and accessible hiring process. 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 please contact 1-855-833-5120. Criminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scams here. Please read our Candidate Privacy Policy. 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. USA Job Seekers: EEO Know Your Rights. Elsevier is a global leader in advanced information and decision support for science and healthcare. We believe that by working together with the communities we serve, we can shape human progress to go further, happen faster, and benefit all. We support continuous discovery and uphold the highest standards of content integrity, reliability, and reproducibility so the communities we serve can advance their field of science, healthcare or innovation with confidence. By combining high-quality content with powerful analytics, we transform complexity into clarity and deliver mission-critical insights that help professionals make better decisions when it matters most. We deliver insights that help research institutions, governments, and funders achieve their goals. We help researchers discover and share knowledge, collaborate, and accelerate innovation. We help librarians provide verified, quality information to universities. We help innovators turn knowledge into new products. We help health professionals improve patient care and educators train the next generation of doctors and nurses. Connecting quality content and innovative technologies, we make progress go further and happen faster. And by championing inclusion and sustainability, we ensure progress benefits all. With 9,500 employees, over 2,300 technologists in 5 major tech hubs, and more than 60 locations across the globe, we are committed to supporting the scientific and healthcare communities around the world. We offer a diverse range of opportunities across technology, commercial, business, and early career jobs. If you are looking for a career that inspires progress in science, innovation and health, and allows you to grow every day, find your team at Elsevier. Elsevier is part of RELX Group. Let’s shape progress together. Join us. elsevier.com/about/careers

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