Senior Machine Learning Engineer for Search

Improve Search and help our customers find the right products.

Senior Machine Learning Engineer for Search

How do you make our customers happy?

With 13 million customers, 129 million monthly visits and about 41 million products on display, bol is the most successful online retail platform in The Netherlands and Belgium. Well over 49,000 external partners enrich the product base. Data-driven and adventurous, bol aims to make life easier and more fun for customers. Its IT professionals support that mission by building and improving the platform, with a culture that values shared learning.

The biggest challenge

Key challenges include integrating complex machine learning models into a low-latency, high-traffic service without compromising performance or scalability. The team is also focused on improving the feedback loop so algorithms can learn and adapt in near real time based on user interactions and changing conditions. Another area of interest is incorporating large language models (LLMs) into the search journey to enhance discovery, relevance, and user experience. The role also explores ways to identify and surface relevant products beyond traditional keyword matching, using techniques such as embeddings and semantic search to better understand user intent and product relationships.

What you will do as Senior Machine Learning Engineer for Search

As a Machine Learning Engineer, you’ll play a key role in designing, building, and deploying machine learning solutions that power bol’s data-driven innovations. Working in cross-functional teams alongside data scientists, software engineers, and business stakeholders, you’ll transform tested models into scalable, real-time production systems that directly enhance customer experiences.

We’re looking for an engineer who can bridge the gap between data science and software engineering—someone who can take ML concepts from idea to production using modern frameworks, MLOps best practices, and cloud technologies. You’ll tackle challenges like integrating low-latency models into high-traffic services, improving real-time feedback loops, and exploring LLM applications for search. Flexibility, curiosity, and a “get things done” mindset are essential as you balance rapid iteration with long-term scalability.

You bring:

• 5+ years’ experience as an ML Engineer, ideally in Search or Recommendations
• Strong Python, SQL, and data engineering skills (Airflow, DBT, Kubernetes, CI/CD)
• Experience deploying ML in production on cloud platforms (GCP preferred)
• Comfortable with agile workflows, A/B testing, and MLOps best practices

Why you can make a difference

Your work will directly influence how millions of customers discover products every day. By turning advanced machine learning models into scalable, real-time search solutions, you will help make search more relevant, intuitive, and efficient. From implementing state-of-the-art retrieval techniques and LLM-powered experiences to improving feedback loops and production systems, your contributions will have a visible impact on both customer satisfaction and business outcomes.

3 reasons why this is (not) for you

Curious pragmatist

• Yes, if you stay current with AI developments but always ask: “How does this solve a real problem?”
• No, if you prefer to wait until ambiguity disappears before moving forward.

Bridging the gap

• Yes, if you like working on the overlap between AI, software, data engineering and data science
• No, if you prefer working on a single, well-defined system with clear specs and minimal cross-team coordination.

Impact that can be seen

• Yes, if you like real-time visible solutions in a high impact area of the company
• No, if you assume to know customers without validating those assumptions.

Where you'll be working

As a Machine Learning Engineer, you’ll be at the centre of a data-intensive landscape. The data science community at bol includes Data Scientists, Machine Learning Engineers, Data Engineers and Software Engineers, alongside a dedicated MLE community. Cross-functional teams with representation from business units provide a complete picture of the organization. The setting is informal, pragmatic and innovative, with success built on collaborating as equals and continuously learning from each other.

Perks of having a blue heart

• 29 days to recharge
• Travel costs: Public transport, car, parking and charging covered
• Pension plan: 75% premium covered
• Annual bonus based on sustainability goals