Job Description
Our client is a company that enables people, enterprises, and cities to harness the power of location. By making sense of the world through the lens of location, it empowers their customers to achieve better outcomes from helping a city manage its infrastructure or an enterprise optimize its assets to delivering drivers to their destination safely. About the Tour Planning Product: Join us in tackling one of the most fascinating challenges in logistics: the Vehicle Routing Problem (VRP). Our client’s Tour Planning solution is the engine behind multi-vehicle route optimization, empowering businesses to design smarter, faster, and more driver-friendly tours. They harness precise and up-to-date map data, real-time traffic insights, road restrictions, and driver preferences to craft tours that are both efficient and practical. The mission is to transform complexity into clarity – delivering solutions that reduce travel time, cut costs, and keep logistics operations running smoothly. Their algorithms factor in every critical detail – driver preferences, delivery time windows, vehicle capacities, and compliance requirements – ensuring that every plan is efficient and meets all constraints. This holistic approach drives cost savings, delivery accuracy, and driver satisfaction while supporting sustainable and compliant operations. If you’re passionate about solving real-world problems at scale, developing sophisticated algorithms, and pushing the boundaries of logistics technology, this opportunity is for you. About the Team: You will join a diverse, passionate team of experts focused on solving complex logistics challenges and delivering impactful solutions. The team values quality, innovation, and continuous improvement. The tech stack includes Rust, Kotlin, Python, AWS, Docker, Kubernetes, and Terraform – empowering the development of scalable, high-performance systems. As a key contributor, you will advocate for end users, define quality standards, and help deliver solutions that make a real difference.
