Senior Software Engineer – Maps Infrastructure

Job description

Job responsibilities

• Manage and operate distributed simulation workflows to support large-scale testing of robotic control, planning, and perception systems in diverse operating scenarios
• Architect and build scalable HD mapping workflows integrated directly into autonomy stacks for control and planning across real-world mapping, localization, and simulation challenges
• Design and build infrastructure and tools to provide high definition (HD) map creation, ingestion, and lifecycle management for autonomous vehicle and robotics development across all of Applied’s products
• Define and own the Dana for Physical AI map storage format to handle heterogeneous features and distributed map data focusing on UIs, data pipelines and storage, CRUD operations, and SDKs
• Design and develop a highly-scalable, high-performance real-time geometric query system to support highly performant three-dimensional spatial queries for vehicle dynamics modeling and testing in autonomous robotic…
• Support tooling to digitize road network geometry, semantic attributes, and related infrastructure from lidar point clouds, high-resolution satellite and aerial imagery, street-level imagery, and other geospatial inputs
• Validate map changes against rigorous mapping specifications to ensure high accuracy, completeness, and consistency of map data thru algorithmic and other quality validation checks
• Support, triage, troubleshoot, and root cause map-related simulation and onroad disengagement system failures by correlating simulation results, dynamics behavior, and autonomy stack outputs

Job requirements

• BS in in Computer Science, Robotics, Applied Mathematics, or related engineering field
• 2+ years of experience in HD mapping for autonomous vehicles building software components or sub systems that address real-world mapping and/or localization challenges
• 3+ years experience in programming & systems including: C++, Python, Go, JavaScript, SQL, Linux, and Git
• Engineering Practices: Scalable distributed systems, CI/CD workflows, version control, and cross-team collaboration using Jira and Git-based tooling
• A strong working understanding of lane-level geometry at CM precision, routing, and HD (High-Definition) map structures used in autonomous driving
• Experience with Kubernetes, AWS, GCP, and/or Azure
• Experience with large-scale data processing using frameworks
• Deep hands-on expertise in relevant algorithms or methods, 3D geometry or distributed systems