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About the Role
Join a team that powers Elsevier’s Data Scientists in Life Sciences, bridging Data Science and Engineering to transform experimental NLP/IR/GenAI models into secure, reliable, and scalable services. You will work on AI-based features, search/ranking quality, and knowledge graph aware retrieval, while enforcing content rights and confidentiality.
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-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 (NDCG, MAP, MRR), LLM quality metrics (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 Data Scientists, Engineers, Subject Matter Experts, Product Managers, and Responsible AI experts to support translate business problems into cutting edge data science solutions
- Collaborate and interface with Operations Engineers who deploy and run production infrastructure
Requirements
- 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
Skills
- GenAI
- ML
- NLP
- IR
- Agentic AI
- RAG
- AWS Sagemaker
- MLflow
- Azure ML
- Elasticsearch
- OpenSearch
- Solr
- Neo4j
- PyTorch
- TensorFlow
- PySpark
Location
- Amsterdam
Work Type
- Full-time
Experience Level
- Senior
Salary/Compensations
- €53,800 - €89,900
Benefits
- Appealing working prospect
- Numerous wellbeing initiatives
- Shared parental leave
- Study assistance
- Sabbaticals
- Country specific benefits
About the Company
- A global leader in information and analytics, helping researchers and healthcare professionals advance science and improve health outcomes.
- Combines 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.
- Work contributes to the world's grand challenges and a more sustainable future.
- Harnesses innovative technologies to support science and healthcare to partner for a better world.
Equal Opportunity
- 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.