Machine learning engineer in logistics

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.

• Architecting and overseeing the development of complex machine learning pipelines for relevant logistics sub-domains
• Implementing and launching Data Science applications with constant improvements using performant and efficient ML models
• Managing both real-time and batch inference systems that are integral to our predictive platforms
• Providing technical leadership and helping to shape best practices across the organisation
• Leading the integration of new technologies and tools into our infrastructure, staying ahead of industry trends
• Ensuring machine learning frameworks remain at the cutting edge of technological advancements
• Collaborating with cross-functional teams to anticipate future needs and recommend long-term solutions that align with business objectives
• Communicating effectively with both technical and non-technical stakeholders, translating complex machine learning concepts into actionable business insights
• Optimising models for production environments to meet the highest standards of efficiency and accuracy at scale
• Working closely with Data Science teams to ensure seamless model deployment and continuous improvement

• Expert-level proficiency with cloud technologies (ideally AWS) and extensive experience with containerisation and orchestration (preferably Kubernetes)
• Deep understanding of software development, DevOps, and MLOps best practices, with a proven track record of applying them in production
• Extensive experience in designing, deploying, and maintaining scalable models and services in production environments
• Strong understanding of Machine Learning, with the ability to collaborate deeply with Data Scientists on model deployment and optimisation
• Experience with MLflow for experiment tracking and model management, and Airflow or Dagster for orchestrating end-to-end ML pipelines and workflows
• Significant experience with Data Engineering, Kafka, and stream processing technologies
• Proficiency in Python and SQL
• Excellent communication skills with the ability to work effectively across technical and non-technical teams
• Proven track record of technical leadership and driving best practices in engineering teams
• Strong problem-solving abilities and a proactive approach to identifying and implementing long-term solutions
• Будет плюсом: experience with additional programming languages is a strong plus

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