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Machine Learning Operations Engineer Make ‘the machine’ work wonders for 13 million customers

Bachelor / Master
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How do you make our customers happy?

With 13 million customers, 30 million monthly visits, and about 33 million products on display, is the most successful online retail platform in the Netherlands and Belgium. And when we say ‘platform’, we mean it. Over 47,000 external partners – and counting – enrich the product base. Data-driven and pioneering (making mistakes is no biggie, as long as learnings are shared), we intend to deliver on our promise to make life easier for customers and partners alike. And that is exactly what our 500 IT professionals (25% internationals), who make up 90+ autonomous Scrum teams, do. Care to help?

The biggest challenge

Although our platform business model may sound familiar, our approach sets us apart from the usual suspects. So much so, in fact, that while we respect the achievements of other international platforms, we don’t necessarily consider them our peers. We opt for a more localized approach (up close and personal!), and our ways of working reflect our idiosyncratic DNA. At, it’s all about autonomy and taking ownership, so end-to-end responsibility isn’t an abstract ambition but the norm. Can you shoulder that?

Your responsibilities as Machine Learning Operations Engineer (MLOps)

  • Develop a deep understanding of business issues and translate insights into data science solutions: you train, test and deploy models and automate the workflow
  • Productionalize models in the Google cloud, set up a compute infrastructure and expose models to the website and (via API’s) our hugely popular mobile apps
  • Optimize models and the data pipeline with data engineering techniques like data storage, OOP improvements, deploying versioning (i.e. with git), and by monitoring training/predictions
  • Develop clean, high-performance, and infinitely scalable applications that allow us to improve the visitor experience each day, every day
  • Build demonstrators for our research and models, and provide insights into model performance through dashboards
  • Uphold best engineering practices and enable your team to grow and succeed, both ‘standalone’ and in relation to stakeholders, to ensure every solution adds value
  • Experiment with brand-new tooling – including tooling you love and add to the stack – and help with prototyping and setting up innovative AI applications

This is an impactful position in our enthusiastic multidisciplinary team, that consists of a product owner, a data scientist/PhD researcher, a data engineer, and an ML engineer. This role challenges you to leverage your Computer Science and Data Engineering knowledge to create and support Machine Learning and Data Science applications that anticipate visitors’ expectations. Together with your colleagues, you design systems to process large data sets intelligently and scalably. You will also collaborate with the data scientists on your team, e.g., to understand which data is required to train and evaluate the models effectively.

To maximize your impact, you need to be intimately familiar with Rust, Kubernetes, Gitlab, Gitlab CI/CD, Bigtable, BigQuery, Spark MLLib on DataProc, Stackdriver, Kibana, Prometheus, and Java with Spring. After all, those tools and techniques are the ‘daily bread and butter’ of the team. That said, the role calls for a tech-inquisitive mindset. Which alternative or new tools have the potential to accelerate our ambitions and business goals? And how can we quantify the added value? We also expect you to discover and dabble in, for instance, PyTorch, Tensorflow, and the AI platform. So if you prefer a ‘stack set in stone’ to pioneering with emerging technologies, this might not be your ideal role. But if you want to ‘boldly go where no MLOps Engineer has gone before’, you’re in for a treat!

3 reasons why this is(n’t) for you

  • Yes, if you’re keen to collaborate with and be inspired by data scientists
  • Yes, if you consider 80% an acceptable clarity threshold – anything over is a bonus
  • Yes, if you are at home in Python and can bring ML models to production
  • No, if you are a true code warrior with little interest in Machine Learning or Data Science
  • No, if you break out in a cold sweat when you coach, convince and align people
  • No, if you are as agile as the Rock of Gibraltar

Where you’ll work

At the premier online retail tech platform in the Netherlands and Belgium. A platform where 13 million Dutch and Belgian customers can choose from over 33 million articles. A platform that helps roughly 47,000 commercial partners run their business. And a platform that will never be ‘finished’, because has been reinventing retail since 1999 and we always will be. If there’s a better way to do something, we’re working on it! Together with our customers, partners, and about 2,400 colleagues. And hopefully together with you! The setting is open, pioneering, informal, and autonomy is actively encouraged. Think ‘tech scale up on steroids’, including the  and international community you associate with that., de winkel van ons allemaal (the store of us all). This is the story we work on every day. It is our belief, that this will grow even stronger when many different people add their uniqueness to our story. We invite you to share your story with us. Because when you bring different people together, the most beautiful things will arise.



What you get

What you get

  • A blue and safe landing

    We warmly welcome our new colleagues, so they feel home as soon as possible. During your onboarding program, we give you all the ins and outs about!
  • Money and more...

    Working at is challenging and therefore you get something in return. Besides salary, you will receive a yearly bonus, holiday allowance, holiday entitlement of 29 days, travel allowance, group insurance and more.

How it works

  1. Carefully, we take a look at your application. Within 2 weeks you know if we invite you for an interview.
  2. We call you to set up an interview. And since we’re already talking: feel free to ask any question you may have.
  3. In this first interview we’ll get to know each other. We want to find out more about you. Work experience is interesting, but we also want to find out more about you as a person. Together, we’ll find out if this job is a match made in heaven.
  4. Before the next interview we will ask you to take an online assessment. We’ll also discuss the position and your team in depth.
  5. 2 interviews are usually enough to see if it’s a match. And if you agree… well, it’s the beautiful beginning of your career at :)

Any questions? Contact

Apply right away Will you make ‘the machine’ work wonders for 13 million customers?

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