Software Engineer (Onboard Maps and State Estimation)
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- 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
- 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
- Rigorous evaluation practice: has built ground-truth or metrics pipelines and used them to hold a shipped operating point and prevent regressions
- 5+ years building production software, including at least one shipped system where they owned the estimation core
- Experience defining a system and its interfaces and negotiating those contracts with consumer teams
- Experience fusing heterogeneous sources such as prior map data, perception output, and raw sensors, into a single world estimate, with rigorous error characterization
- State estimation fundamentals proven in production: factor graphs and/or filtering, data association, uncertainty representation and propagation, and 3D geometry and transforms
- Strong modern C++ and the ability to make estimation code meet real-time budgets on embedded compute
- Judgment about uncertainty: understands the difference between an error that degrades gracefully and one that is catastrophic, and designs the system accordingly
- 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