Machine Learning Engineer

Posted 4 Days Ago
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Hiring Remotely in Office, Machaze, Manica, MOZ
Remote
Entry level
Marketing Tech • Software
The Role
Designs, develops, trains, deploys, and operates machine learning models and infrastructure for consumer pricing. Responsibilities include demand elasticity estimation, causal modeling, simulation, pricing policy optimization, scalable inference, monitoring, MLOps adoption, and collaboration with data scientists, engineers, and product stakeholders.
Summary Generated by Built In
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

Skills Required

  • Strong experience developing machine learning infrastructure platforms for consumer pricing and policy-related products
  • Experience developing predictive and causal data science models
  • Hands-on experience with Python, pandas, NumPy, scikit-learn, and TensorFlow
  • Proficiency in Python and software engineering principles, including object-oriented design, design patterns, and testing
  • Experience designing and operating production machine learning systems beyond notebook-based training
  • Familiarity with REST APIs, batch inference, and event-driven architectures
  • Experience productizing and deploying models using cloud-native ML platforms such as AWS SageMaker or GCP Vertex AI
  • Familiarity with Airflow, MLflow, and Docker
  • Understanding of data engineering fundamentals, including SQL and distributed data processing
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The Company
HQ: Amsterdam
15,313 Employees

What We Do

Just Eat Take​away​.com is a lead­ing glob­al online food deliv­ery mar­ket­place, con­nect­ing con­sumers and restau­rants through our plat­form in 20 coun­tries. Like a dinner table, working at JET brings our office employees and couriers together. From coding to customer service to couriers, JET is a fun, fast-paced and supportive place where you can be yourself. No day is the same. Our days are filled with new experiences. We see every challenge that comes our way as a chance to grow, both the business, and ourselves. We’re connected to millions of food-lovers, hundreds of thousands of connected partners and some of the best-known brands of the planet. When you take your seat here, you’ll find that a simple scribble on a napkin can turn into something seen by millions. Together we transform, create, reinvent and empower every food moment. As a leading online food tech company, JET brings together the stability of a global business, with the agility of a start-up. We got here by always staying one step ahead of the competition. So load up your plate with ideas that get you excited, because at JET everything is on the table. https://careers.justeattakeaway.com

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