Machine Learning Engineer III, Routing Cost

Job description

Mapbox is the leading real-time location platform for a new generation of location-aware businesses. Mapbox is the only platform that equips organizations with the full set of tools to power the navigation of people, packages, and vehicles everywhere. More than 4 million registered developers have chosen Mapbox because of the platform’s flexibility, security and privacy compliance. Organizations use Mapbox applications, data, SDKs and APIs to create customized and immersive experiences that delight their customers. What We Do The Navigation team at Mapbox develops and operates web services powering virtually all of Mapbox’s strategic navigation initiatives in consumer, automotive, and logistics verticals. We are a highly multidisciplinary organization, with work spanning distributed systems on AWS to geospatial localization, traffic telemetry, and mapping. Collectively we are revolutionizing in-car experiences with technology to build fast, industry-leading maps and navigation for any vehicle. We’ve launched products such as MapGPT , Mapbox for EV , and we’re enhancing the visual experience of in-vehicle navigation with 3D styling with our new Mapbox Standard through web and mobile SDKs. Mapbox has worked with automotive partners — including BMW, Toyota, and GM — to bring the best aspects of mobile app development into in-vehicle navigation and infotainment. Mapbox Blog: Introducing 3D Live Navigation Mapbox Blog: Route Notifications Improve Driver Safety Mapbox Newsroom: AI Features in New Navigation SDK As AI becomes embedded in modern engineering workflows, we value engineers who can thoughtfully integrate AI into design, development, and decision-making. Our interview process will include discussion of how you use AI in your engineering workflow. What You’ll Do As a Machine Learning Engineer III on the Routing Cost team, you will lead the design, development, and delivery of highly trafficked recommendation systems for our routing cost engine. Your technical contributions will include: Lead the engineering team(s) to execute end-to-end feature implementation within the larger navigation organization (~80 engineers). Design and build new ML and data pipelines, as well as optimizing existing ML and data pipelines. Build tools for automated quality assurance and data exploration. Leverage geospatial algorithms to optimize pipelines, as well as creating aut…