ML Engineer - Research Products (Hybrid, Amsterdam) Department: Data ScienceAmsterdam - Hybrid About the Role Our client is seeking an ML Engineer to help build and scale the AI technologies behind large‑scale research platforms used across academia, government, and scientific/technical publishing. You will operate at the intersection of Data Science, ML Engineering, Search, and Generative AI, transforming experimental NLP/IR/RAG/LLM models into secure, reliable, production-grade services. The systems you'll work on operate over a vast database, requiring excellence in search quality, recommendation engines, evaluation pipelines, and knowledge-graph‑aware retrieval-all while ensuring strict content rights and confidentiality. Key Responsibilities ML & LLM Engineering, Search & Recommendations Automate and orchestrate end-to-end ML workflows across cloud and AI platforms (AWS, Azure, Databricks, foundation model APIs).Maintain and version-controlled model registries and artifact stores to support reproducibility and governance.Develop CI/CD for ML, including automated validation, model testing, and deployment.Build ML Engineering solutions using platforms such as AWS SageMaker, MLflow, or Azure ML.Develop custom SageMaker pipelines for recommendation systems.Engineer the components of RAG/GAR systems, including embeddings, query handling, chunking, hybrid retrieval, prompt libraries, structured outputs, and guardrails.Build ML pipelines leveraging Elasticsearch/OpenSearch/Solr, vector databases, and graph databases.Design evaluation pipelines covering offline IR metrics (e.g., NDCG, MAP, MRR), LLM metrics (faithfulness, grounding), and A/B testing.Monitor and optimize infrastructure costs and resource usage.Stay current with developments in NLP, LLMs, RAG, and Generative AI and apply state‑of‑the‑art techniques in experiments and production systems. Requirements 4+ years' experience in ML Engineering, shipping ML, search, or GenAI systems to production.Strong Python skills (required); Java or Scala is a plus.Background in machine learning theory, statistical analysis, and NLP.Hands-on experience with major cloud platforms (AWS( preference), Azure, GCP).Experience with search, vector, or graph technologies (e.g., Elasticsearch, OpenSearch, Solr, Neo4j).Familiarity with evaluating LLM models.Experience with scholarly publishing workflows, bibliometrics, or citation graphs is advantageous.Strong understanding of the Data Science life cycle, including feature engineering, training, and evaluation.Experience with ML frameworks such as PyTorch, TensorFlow, and PySpark.Comfortable with large-scale data systems such as Spark. Benefits & Working Style The client promotes a balanced, flexible hybrid work culture and offers a range of wellbeing and professional development benefits, including:A generous salary on a 36-hour work week - We are hiring Medior-Senior candidates, so please apply as our range is flexible. Comprehensive pension scheme & excellent tertiary benefits. Does this job sound promising to you?Apply online now, or call ✆ 0611732627 Let op: vacaturefraude Helaas komt vacaturefraude steeds vaker voor. We waarschuwen je voor mogelijke misleiding: * Wij zullen nooit via WhatsApp of in een videogesprek vragen om jouw persoonlijke gegevens (zoals een kopie van je ID, bankgegevens of BSN). * Twijfel je over de echtheid van een vacature of contactpersoon? Neem dan altijd rechtstreeks contact met ons op via de officiële contactgegevens op onze website. Important: job fraud Unfortunately, job fraud is becoming more common. Beware of such scams: * We will never ask for personal information (such as a copy of your ID, bank details, or social security number) via WhatsApp or during a video call. * If you're unsure whether a vacancy or contact person is legitimate, please reach out to us directly using the official contact details on our website.