About the Role

Applied Intuition is looking for software engineers to help build HD maps infrastructure for autonomous vehicles. You bring curiosity and a growth mindset and we’ll teach you mapping concepts along the way.

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

• Build scalable HD mapping workflows integrated directly into autonomy stacks for control and planning across real-world mapping, localization, and simulation challenges

• 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

• Contribute to 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

• 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

• Collaborate with engineers and customers to gather requirements, plan features, and create roadmaps

Requirements

• BS in in Computer Science, Robotics, Applied Mathematics, or related engineering field

• 2+ 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

Preferred Qualifications

• Experience with Kubernetes, AWS, GCP, and/or Azure

• Experience with large-scale data processing using frameworks

• Experience using browser-based map editors or web-based 3D tooling

• Robotics & Simulation: Robot Operating System (ROS), Unreal Engine, MATLAB, Blender

• Autonomy Domain Expertise: Simulation-based testing, verification, and validation of autonomous robotic platforms and family with HD maps and map management pipelines.