ML Engineer – Research Products (Hybrid, Amsterdam)

Department: Data Science

Amsterdam - 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