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Salary: USD 228,000 - 285,000 / annual
Rivian is seeking a Staff Geospatial Software Engineer to lead the architectural evolution of geospatial data preparation and routing infrastructure for its Large Driving Model (LDM). This is a high-impact position at the intersection of spatial data engineering, graph algorithms, and production-grade AI infrastructure for autonomous vehicles.
You will design and optimize high-throughput route processing systems, map-matching algorithms, and data pipelines that transform raw spatial topology into ML-ready representations for both onboard and offboard systems. Your work will directly support Rivian's autonomous driving capabilities by ensuring seamless integration between map data and model inputs.
Key responsibilities include:
- Designing and owning the route processing pipeline architecture that serves as the foundational data preparation layer for the LDM
- Leading integration, customization, and optimization of spatial frameworks and routing engines to support complex driving scenarios
- Establishing techniques to clean, validate, align, and enrich map features, minimizing discrepancies between training and deployment data
- Partnering with ML Infrastructure, Motion Planning, Localization, Mapping, and Simulation teams to define clean data interfaces
- Acting as a key technical authority on route data processing and spatial graph architecture
- Mentoring junior engineers, establishing best practices, and defining the long-term roadmap for spatial data handling
- Championing production-grade C++ and Python code quality, ensuring the codebase is modular, scalable, thoroughly tested, and performant
Requirements:
- B.S., M.S., or Ph.D. in Computer Science, Robotics, Electrical Engineering, or related technical field
- 8+ years of industry experience developing high-performance route processing algorithms, GIS/spatial data pipelines, or routing systems for autonomous platforms or large-scale mapping products
- Expert-level proficiency in production-grade C++ (data structures, memory management, multi-threading) and Python for data engineering, automation, and rapid prototyping
- Deep technical foundation in spatial graph algorithms (A*, Dijkstra, contraction hierarchies), map-matching, spatial indexing, and topological data manipulation
- Hands-on experience with OpenStreetMap (OSM) data structures and modern open-source routing engines (e.g., Valhalla, OSRM) is a strong plus
- Familiarity with localization concepts, spatial coordinate transformations, and HD/SD map abstractions within autonomous driving stacks
- Proven track record leading complex software projects, building technical consensus, and mentoring engineering peers
- Proactive approach to identifying data bottlenecks and designing robust algorithmic solutions
