Senior Machine Learning Engineer (MLOps)

TL;DR

Senior Machine Learning Engineer (MLOps): Bringing AI systems into production on one of the largest knowledge datasets in the world with an accent on reliability, scalability, and reproducibility. Focus on designing, building, and managing ML systems in production, influencing pipelines, evaluation, tooling, and team collaboration.

Location: Hybrid (Amsterdam office 1-2 days per week) + 20 days per year working remotely from abroad

Salary: €95,000 to €120,000 + 5% profit share bonus

Company

Globally operating organization that has been shaping how knowledge is stored, enriched and unlocked for decades, building AI systems (search, RAG, Agentic AI, reasoning) used directly by millions of users.

What you will do

• Bring AI systems into production on one of the largest knowledge datasets in the world.
• Work in hybrid squads alongside data scientists, software engineers, product owners and Responsible AI specialists.
• Design, build and manage ML systems in production, from scratch to deployment.
• Work on systems such as GAR+RAG pipelines, search & ranking using Elasticsearch/OpenSearch, and prompt libraries for LLMs.
• Keep a sharp eye on the landscape: the latest developments in GenAI, NLP and RAG you translate into concrete experiments and systems.
• Influence how pipelines, evaluation, tooling and team collaboration are set up.

Requirements

• At least 4 to 6 years of experience in ML Engineering or MLOps, with a proven track record of personally designing, building and managing ML systems in production.
• Strong programming skills in Python.
• Completed technical MSc or higher.
• Solid foundation in GenAI: you understand how LLMs work, know the architectural trade-offs and can discuss them technically.
• Hands-on experience with AWS.
• You think in systems, not just models.

Nice to have

• Experience with Azure or GCP alongside AWS.
• Hands-on with MLOps platforms such as AWS SageMaker, MLflow or Azure ML.
• Working experience with LangChain and/or LangGraph.
• Experience with search and retrieval technologies: Elasticsearch, OpenSearch, Solr, vector databases or graph databases (e.g. Neo4j).
• Experience with ML frameworks such as PyTorch, TensorFlow or PySpark.

Culture & Benefits

• €95,000 to €120,000 (based on 36 hours) + 5% profit share bonus.
• 36-hour working week (full-time), salary includes 8% holiday allowance and 13th month.
• 50% working from home + flexible hours (1 to 2 days in the Amsterdam office).
• 20 days per year working from abroad.
• 25 vacation days + option to buy more via PKB.
• Visa sponsorship (HSM) available.