Senior Machine Learning Engineer - Logistics Optimization

Delivery Hero — Germany · Posted ~2 hours ago

Senior Full-time Visa History ✓

Skills

Machine learning Data science Optimization algorithms Python ML model development Machine Learning Data Science

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Summary ✨ AI‑Generated

A senior machine learning engineer is needed to develop scalable ML models for complex optimization problems. The role focuses on improving operational efficiency through advanced algorithms and data-driven solutions.

Highlights

Opportunity to build machine learning solutions that optimize large-scale logistics operations and directly influence business performance.

Description

Job DescriptionWe are on the lookout for a Senior Machine Learning Engineer to join the Logistics Optimization team on our journey to always deliver amazing experiences. The Optimization Tribe's purpose is to maximize Delivery Hero's logistics performance. We achieve this by owning and continuously improving the sophisticated algorithm that solves the real-time vehicle routing problem, assigning orders efficiently every second across the world. This directly impacts DH's core efficiency and customer satisfaction KPIs, influencing decisions for stakeholders from Operations to Product. As an ML Engineer, your value lies in tackling the problems at scale head-on and building ML models and products which shape the algorithm's logic and decisions to meet our long-term goals of best-in-class efficiency and service, making a tangible impact across the Delivery Hero network. Are you ready to take your Machine Learning Engineering and Data Science skills to the next level and make a tangible impact on millions of users worldwide? In this role you will, Build and Maintain: Design, build and maintain scalable ML models services, optimizing for performance and efficiency. Design Robust Architecture: Build the infrastructure that powers critical model inputs fed every minute to the dispatch algorithm which shapes experiences for millions of customers across the globe, every single day. Collaborate and Optimize: Work closely with data scientists and engineers to understand their product needs and build scalable solutions. Develop Tooling: Build and enhance ML engineering tooling for Model Development, Monitoring, Serving, and Experimentation. Leverage Cloud: Utilize DH cloud infrastructure built with modern technologies on popular cloud platforms to build highly available systems for multiple teams. Innovate and Suggest: Proactively suggest how the team can leverage new technologies and architectures to support new use cases.