AIM
Senior SLAM Engineer
Seattle · Senior
Sponsorship not specifiedDetected 41 days ago
PythonC++ReactAlgorithmsMachine LearningRoboticsAerospace EngineeringElectrical EngineeringSensors
About the role
- We replace decades of manual, error-prone, high-risk work with intelligent machines that reshape how earthmoving is done.
- Our machines must know precisely where they are in complex, constantly changing environments: terrain that is being actively dug, moved, and reshaped by the machines themselves.
- Unlike road vehicles that can rely on static HD maps and distinct lane lines, AIM machines operate in dynamic, often feature-poor landscapes.
Requirements
- Bachelor's or Master's degree in Computer Science, Robotics, Electrical Engineering, Aerospace Engineering, or a related field.
- Deep expertise in modern state estimation techniques (e.g., Extended/Unscented Kalman Filters, Particle Filters) and optimization frameworks (e.g., GTSAM, Ceres Solver, g2o).
- Experience with LiDAR odometry and mapping (LOAM variants), point cloud registration (ICP, NDT), and handling large 3D point clouds.
- Experience tightly coupling IMU data with LiDAR, visual, or GNSS measurements.
- Experience debugging complex, real-world robotic system behavior using data, logs, and performance metrics.
- Experience working in robotics.
- 5+ years of professional experience building SLAM, state estimation, or localization systems.
- Strong mathematical foundation in 3D geometry, linear algebra, probabilistic robotics, kinematics, and optimization.
- Hands-on experience developing and maintaining automated sensor calibration pipelines (intrinsic, extrinsic, and spatio-temporal) for multi-sensor suites (LiDAR, Camera, IMU, GNSS).
- Exceptional programming ability in modern C++ (C++14/17 and beyond) and Python for tooling/analysis.
Nice to have
- Experience dealing with complex vehicle kinematics and severe wheel/track slip.
- Familiarity with handling map obsolescence in dynamic environments.
Company info
- 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.
- This creates novel challenges in Simultaneous Localization and Mapping (SLAM), state estimation, and sensor fusion.
- We're building the SLAM systems that allow machines to navigate reliably, build accurate topographical representations on the fly, and operate safely under harsh physical conditions.
- We're growing fast, scaling globally, and building the engineering foundation that will define the next century of construction.
- Learn more about AIM here. https://aim.vision/about
- You're an engineer who is ready to take one of the most difficult state estimation and mapping problems where algorithmic theory meets the messy, physical world.
- You have experience building production SLAM or state estimation systems that are proven to work on real hardware.
- You understand how localization algorithms behave under real-world constraints such as severe sensor vibration, track/wheel slip, GPS-denied environments, and featureless terrain.
- You enjoy working across the full localization stack - from designing 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, not just algorithms.
- You debug deeply, validate rigorously, and iterate quickly using field data to continuously improve system robustness.
- You're motivated by building state estimation systems that enable safe, reliable autonomy in environments where failure is not acceptable.
- About us together
- We are solving SLAM problems that do not exist in traditional autonomy domains.
- AIM machines operate in environments that are constantly evolving - digging soil, moving rock, loading trucks, and reshaping terrain.
- These environments introduce challenges such as:
- Dynamic terrain
- Feature-poor environments
- Sensor occlusion
- Dust, and environmental noise
- Vibration and degrading calibration
- We will design algorithms that perform reliably in these environments.
- We will build SLAM systems that integrate tightly with perception, planning, controls, and machine operations.
- And we will continuously close the loop between field data and algorithm improvements.
- If that excites you - you're the kind of Senior SLAM Engineer who will thrive here.
This listing is sourced directly from AIM's careers page and normalized into a canonical job model.