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Open nowPosted yesterday

Machine Learning Engineer

takeaway127 open roles

Where
Amsterdam Office
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Your applicationOpen nowMachine Learning Engineertakeaway · Amsterdam Office

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The clock on this job

Early applications get read.

13.4% of postings close within 7 days. Measured by our own scanner across the market. takeaway postings stay open a median of 12 days.

Share of postings closed within
  1. 2.2%1 day
  2. 4.6%3 days
  3. 13.4%7 days
  4. 21.6%14 days
  5. 36.2%30 days
  6. 59.0%60 days
This job: posted yesterday

takeaway median: 12 days open

The posting

Ready for a challenge?

Then Just Eat Takeaway.com might be the place for you. We're a leading global online delivery platform, and our vision is to empower everyday convenience. Whether it's a Friday-night feast, a post-gym poke bowl, or grabbing some groceries, our tech platform connects tens of millions of customers with hundreds of thousands of restaurant, grocery and convenience partners across the globe.

About this role

We are looking for a Machine Learning Engineer with passion for using machine learning to create intelligent applications. As a Machine Learning Engineer, you will be part of the Pricing Data Team inside the User Behavior Data Team under the umbrella of Data and Analytics pillar with 500+ data engineers, analysts, scientists.

You will collaboratively design, build and will focus on evolving existing machine learning and AI capabilities across the platform, improving those capabilities, and innovating new ones for the future. As a member of the Pricing Data Team, you will develop solutions to estimate demand price elasticity and generate counterfactuals through simulation, finally optimize consumer pricing policy to ensure a reliable, efficient, and revenue generated service.

These are some of the key components to the position:

  • Design, develop, and train data science models to solve complex business problems, taking full end-to-end ownership from initial prototyping to production deployment.
  • Strong knowledge of regression, boosting gradient, causal inference data science models, feature engineering and evaluation of model performance.
  • Develop the architectural design of ML systems, building both the core algorithmic training pipelines and the scalable inference and monitoring infrastructure.
  • Collaborate extensively along with other Data Scientists, Data Engineers, and Product stakeholders to bridge the gap between model development and production systems.
  • Drive the adoption of MLOps best practices (e.g., CI/CD for ML, model versioning, feature stores) to accelerate the feedback loop for Data Scientists.
  • Communicate the complexities of ML systems (e.g.,e.g., algorithmic choices, latency vs. accuracy trade-offs) effectively to both technical and non-technical stakeholders.
  • Build and maintain a strong network across the Data and Engineering organizations to ensure ML systems integrate seamlessly with the wider platform.

What will you bring to the team?

  • Strong experience in machine learning, specifically developing ML infrastructure platforms for consumer pricing and policy-related products.
  • Hands-on experience developing data science models (predicting and causal modelling) using Python libraries such as pandas, NumPy, scikit-learn, and TensorFlow.
  • Proficiency in Python and a strong understanding of software engineering principles (object-oriented design, design patterns, testing) applied to ML.
  • Demonstrable experience designing and operating ML systems in production (beyond notebook-based training), including familiarity with serving patterns such as REST APIs, batch inference, and event-driven architectures.
  • Ability to work independently and solve complex problems, with a proven track record of productising and deploying models using cloud-native ML platforms (e.g., AWS SageMaker, GCP Vertex AI).
  • Familiarity with orchestration, tracking, and containerisation tools, particularly Airflow, MLflow, and Docker.
  • Solid Understanding of data engineering fundamentals (e.g., SQL, distributed data processing) to debug and optimise data flows.

At JET, this is how we play

Our teams forge connections internally and work with some of the best-known brands on the planet, giving us truly international impact in a dynamic environment. Being the best at what we do isn't just about delivering on our strategy. It's a competition for something incredibly valuable – our customers' choice. Every time a customer decides where to order, they're picking a side. At the heart of the JET Customer League are our values and behaviours. They guide every interaction, every decision, every innovation. These are the actions we need to perform consistently and brilliantly, to surpass the competition and earn our customers' loyalty, again and again. Fun, fast-paced and supportive, the JET culture is about movement, growth, helping one another to succeed and celebrating wins. By truly living our values and embodying our behaviours, we're building a customer-first culture which enables us to stay one step ahead of the competition.

Inclusion, Diversity & Belonging

No matter who you are, what you look like, who you love, or where you are from, you can find your place at Just Eat Takeaway.com. We're committed to creating an inclusive culture, encouraging diversity of people and thinking, in which all employees feel they truly belong and can bring their most colourful selves to work every day.

What else is cooking?

Want to know more about our JETers, culture or company? Have a look at our career site where you can find people's stories, blogs, podcasts and more JET morsels.

Are you ready to take your seat? Apply now!

#LI-NB2

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