Software Engineer - Onboard Maps and State Estimation

About the role

Our Localization, Calibration, and Mapping team delivers high-integrity solutions that let autonomous systems navigate with precision in real-time, safety-critical environments — across consumer automotive, trucking, mining, and construction. As a new team focused on platformization, we offer a rare opportunity to own core work leveraged across the entire organization.

HD maps go stale the moment they're built — lanes get repainted, stop lines move, roads close. You'll own the live map on Applied's onboard stack: a real-time fused estimate of the world built from map priors and live perception, from the estimation core to the change-detection and trust semantics the planner consumes, across every vehicle vertical we serve. This layer is early and has no incumbent design. You'll set the architecture and define the interfaces rather than tune inside someone else's system. We encourage engineers to take ownership of technical and product decisions and to interact closely with users to collect feedback.

At Applied Intuition, you will:

• Own the onboard live-map estimator end to end: fuse HD map priors with live perception into a single, real-time estimate of the world the rest of the stack can trust

• Build our onboard map change detection: classify situations like boundary shifts, stop-line moves, and road closures from the divergence between map and perception, and define when the planner should stop trusting the map

• Define the map trust contracts the planner builds against: confidence semantics, degraded-mode behavior, and the operating points that hold across vehicle programs

• Build the evaluation backbone, ground-truth and metrics pipelines, operating points, and regression testing that keep estimator and detector quality from silently drifting

• Ship estimation code in modern C++ that meets real-time budgets on embedded compute

• Extend the loop offboard over time: aggregate divergence detections across fleet drive logs into map freshness and correction pipelines

We're looking for someone who has:

• 5+ years building production software, including at least one shipped system where they owned the estimation core

• State estimation fundamentals proven in production: factor graphs and/or filtering, data association, uncertainty representation and propagation, and 3D geometry and transforms

• Experience fusing heterogeneous sources such as prior map data, perception output, and raw sensors, into a single world estimate, with rigorous error characterization

• Strong modern C++ and the ability to make estimation code meet real-time budgets on embedded compute

• Rigorous evaluation practice: has built ground-truth or metrics pipelines and used them to hold a shipped operating point and prevent regressions

• Judgment about uncertainty: understands the difference between an error that degrades gracefully and one that is catastrophic, and designs the system accordingly

• Experience defining a system and its interfaces and negotiating those contracts with consumer teams

Nice to Have:

• Map change detection or live/lifelong mapping experience

• HD map semantics: lane graphs, topology, map formats and their failure modes

• GTSAM or comparable factor-graph frameworks; Lie group methods

• Degraded-mode or integrity-monitor design for a safety-relevant function

• MS/PhD with a focus on state estimation or SLAM