Machine learning engineer for delivery platforms

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. 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 Data Science team inside the Product and Tech group with +2200 brilliant developers, engineers, analysts and researchers.

• Researching, implementing, and deploying innovative ML techniques applicable to logistics problems.
• Scaling and transferring novel machine learning solutions to improve our decision making processes and solutions in their different product use cases.
• Implementing and launching Data Science applications that coordinate with front facing solutions; constant improvements using performant and efficient ML models.
• Implementing tools, data pipelines, and evaluation frameworks to enable development, iteration, and launch of ML ideas within the product scope.

• Strong experience in Machine Learning, developing real time data streaming technologies for forecast or logistics products.
• Strong coding and software engineering skills in Python.
• Able to work independently and solve complex problems, with a demonstrated ability to productise and deploy using cloud services (e.g. Amazon Web Services, Google Cloud Platform).
• Strong background in working with microservices and event-driven architecture, serverless computing, and cloud architecture patterns.
• Familiarity with tools and packages including Kubernetes (deployment in production) is expected.
• Experience collaborating closely with multi-functional teams, driving forward best practices.
• Будет плюсом: A plus would be additional experience with Airflow/Mlflow/Docker/Flink; Real-time production systems at scale (millions of requests/transactions per day) is desirable

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