SLAM Engineer

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.

As a Senior SLAM Engineer, you will design, develop, and deploy the state estimation, mapping and calibration systems that allow AIM’s autonomous machines to navigate and understand their changing environment.

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, including 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.

Design, build, and maintain automated calibration pipelines for complex multi-sensor rigs (LiDAR, Camera, INS/IMU).

Develop algorithms for online and offline intrinsic, extrinsic, and spatio-temporal calibration to ensure high precision despite severe machine vibration and mechanical wear.

Create scalable calibration routines that can be executed by field operators on active jobsites without needing specialized laboratory environments.

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 of machines.

Collaborate with perception, planning, and controls teams to provide stable, continuous state estimates required 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.

Analyze real-world telemetry and logs collected from deployed machines to characterize drift, analyze loop-closure failures, and improve system reliability.

Identify edge cases and failure modes and develop robust, mathematically sound solutions.

Work closely with field engineers and operators to validate localization performance under real, punishing operating conditions.