About the Role

Applied Intuition is looking for senior software engineers with passion and expertise in owning and maintaining HD maps infrastructure for autonomous vehicles.

At Applied we treat maps not as a static dataset, but as a single integrated, self-healing data flywheel powering Physical AI. Fleets of vehicles collect ground truth from multimodal sensors which feed ingestion pipelines, dynamic change detection algorithms, machine learning models, and real-time onboard localization and map fusion -closing the loop between field data collection and instantaneous autonomy stack updates.

In this full time role on the Maps team, you will solve challenges at the intersection of large-scale distributed systems, continuous data pipelines, and spatial visualization. You'll be involved in whole life cycle of HD maps from gathering and codifying map requirements, supporting map visualization and editing, enabling large scale simulations, and publishing maps to AV fleets across multiple vehicle types worldwide - from long-haul L4 commercial trucks to L2++ personal cars, to heavy mining rigs, and tactical defense platforms. Our mission is to add intelligence to 1 billion machines.

Key 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 platforms
• 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
• Collaborate with engineers and customers to gather requirements, plan features, and create roadmaps
• Advise customers on the effective use of simulation and mapping tools to evaluate autonomy performance, safety, and system robustness

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

Preferred Qualifications

• 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
• Deep understanding of sensors used for localization, state of the art industry solutions, and common approaches for production systems
• Experience working with point cloud data, 3D visualization environments, or lidar-based annotation tools
• Experience using browser-based map editors or web-based 3D tooling
• Familiarity with feedback loops between mapping, perception, localization, and planning teams
• Familiarity with log-based resimulation tooling and simulation-based map validation
• Robotics & Simulation: Robot Operating System (ROS), Unreal Engine, MATLAB, Blender
• Autonomy Domain Expertise:
  
  • Robotic mapping systems, HD maps, and map management pipelines
  • Simulation-based testing, verification, and validation of autonomous robotic platforms
  • Autonomous control, motion planning, and perception systems
  • Experience querying data across global-sized HD maps, including visualization

Don't meet every single requirement? If you're excited about this role but your past experience doesn't align perfectly with every qualification in the job description, we encourage you to apply anyway. You may be just the right candidate for this or other roles.