AIM delivers autonomous earthmoving for mining, construction, and defense. Transform your fleet with AI-powered machines that maximize productivity and safety. Backed by General Catalyst and Khosla.
About the role
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.
What they're looking for
- Bachelor’s or Master’s degree in Computer Science, Robotics, Electrical Engineering, Aerospace Engineering, or a related field
- 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
- Deep expertise in modern state estimation techniques (e.g., Extended/Unscented Kalman Filters, Particle Filters) and optimization frameworks (e.g., GTSAM, Ceres Solver, g2o)
- 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
More about this role
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. We replace decades of manual, error-prone, high-risk work with intelligent machines that reshape how earthmoving is done.
Localization and mapping are core capabilities of our autonomy platform. 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. 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...
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