1 day ago
Amsterdam, Netherlands or London, United KingdomSenior
Responsibilities
- Automate and orchestrate ML workflows across AWS, Azure, Databricks, and foundation model APIs such as OpenAI.
- Maintain model registries and artifact stores for reproducibility and governance.
- Develop CI/CD for ML, including data validation, model testing, and deployment automation.
- Implement MLOps solutions and custom SageMaker pipelines for recommendation systems.
- Build engineering components for RAG and Generative AI systems, including retrieval, embeddings, prompt libraries, guardrails, and structured LLM output.
- Design ML pipelines using search, vector database, and graph database technologies.
- Build offline information-retrieval, LLM-quality, and A/B evaluation pipelines.
- Optimize infrastructure costs through monitoring, scaling strategies, and efficient resource utilization.
- Collaborate with Data Scientists, Product Managers, Responsible AI experts, subject-matter experts, and Operations Engineers.
Requirements
- 3–5+ years of experience in ML Engineering, MLOps platforms, or shipping ML, search, or Generative AI systems to production.
- Strong Python, Java, and/or Scala engineering skills.
- Experience with statistical analysis, machine learning theory, and natural language processing.
- Hands-on experience with AWS, Azure, and/or Google cloud solutions.
- Experience with search, vector, and graph technologies such as Elasticsearch, OpenSearch, Solr, and Neo4j.
- Experience evaluating LLM models.
- Background in scholarly publishing workflows, bibliometrics, or citation graphs.
- Strong understanding of the Data Science Life Cycle, including feature engineering, model training, and evaluation metrics.
- Familiarity with PyTorch, TensorFlow, PySpark, and large-scale data processing systems such as Spark.
Benefits
- Wellbeing initiatives, shared parental leave, study assistance, and sabbaticals are offered.
- The role supports flexible working hours.
- The position is based in Amsterdam, Netherlands, and is covered by the Collective Labor Agreement Publishing Industry.
Tech Stack
Categories
About Elsevier
Elsevier builds scientific and medical information products and analytics platforms for researchers, clinicians, and educators. Its portfolio includes journals and databases such as The Lancet, Cell, ScienceDirect, Scopus, and ClinicalKey, sold primarily via institutional subscriptions, licensing, and open-access publishing fees. Founded in 1880 and headquartered in Amsterdam, Elsevier operates as a business of RELX, serving universities, hospitals, corporations, and government research agencies worldwide.