Senior SLAM Engineer
Aim · Seattle
About this role
## Senior SLAM Machine Learning Engineer ### About AIM AIM builds autonomy for the real world—robots that move mountains. Our systems fuse software, hardware, robotics, and mission-critical infrastructure into ruggedized, safety-critical machinery operating on jobsites across the world. Localization and mapping are core capabilities of our autonomy platform. AIM machines must know precisely where they are in complex, constantly changing environments (terrain being actively dug, moved, and reshaped). Unlike road vehicles that can rely on static HD maps and distinct lane lines, AIM machines operate in dynamic, often feature-poor landscapes—creating novel challenges in **Simultaneous Localization and Mapping (SLAM)**, **state estimation**, and **sensor fusion**. ### About you You’re an engineer ready to tackle difficult state estimation and mapping problems where algorithmic theory meets the messy, physical world. You have experience building **production SLAM or state estimation systems** proven to work on real hardware. You understand how localization behaves under real-world constraints such as: - Severe sensor vibration - Track/wheel slip - GPS-denied environments - Featureless terrain You enjoy working across the full localization stack—from sensor configuration, integration, and calibration (IMU, LiDAR, GNSS, kinematics), through factor graph optimization and map management, to deployment on edge compute for real-time control loops. You take ownership of outcomes: you debug deeply, validate rigorously, and iterate quickly using field data to continuously improve robustness. ### What you will own As a **Senior SLAM Engineer**, you will design, develop, and deploy state estimation, mapping, and calibration systems that allow AIM’s autonomous machines to navigate and understand their changing environment. **1) Design & Advance SLAM Systems** - Architect and develop robust multi-sensor fusion algorithms (LiDAR, IMU, GNSS, wheel odometry/kinematics) for high-frequency, low-latency state estimation - Advance AIM’s mapping stack: point cloud registration, loop closure, and dynamic map updating - Develop algorithms to detect and react to outlier measurements caused by dust, sliding terrain, or sensor degradation **2) Own Sensor Calibration Pipelines** - Design, build, and maintain automated calibration pipelines for complex multi-sensor rigs (LiDAR, Camera, INS/IMU) - Develop online and offline intrinsic, extrinsic, and spatio-temporal calibration to maintain high precision despite vibration and mechanical wear - Create scalable calibration routines executable by field operators on active jobsites **3) Build Production Localization Systems** - Implement and optimize multi-modal localization algorithms (graph or filter based) for real-time deployment on edge hardware - Build scalable tools for map management, alignment, and distribution across fleets **4) Integrate SLAM with the Autonomy Stack** - Collaborate with perception, planning, and controls teams to provide stable, continuous state estimates for precise heavy-duty manipulation and navigation - Ensure SLAM outputs interact safely with machine-centric awareness and safety systems - Design localization interfaces that are robust, testable, and observable **5) Use Field Data to Improve System Performance** - Analyze telemetry and logs to characterize drift, analyze loop-closure failures, and improve reliability - Identify edge cases and failure modes and develop robust, mathem
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