Robotics Engineer

Treeswift Inc•New York, NY

1d•$150 - $200

About The Position

As a senior robotics engineer you will drive outcomes across perception, mapping, sensor fusion and calibration that directly contribute to the expansion of our business. As our business grows these needs will change; first priorities for this role will include: Improving the quality and consistency of our product in an increasing breadth of operating conditions. For example, you will lead SLAM development including incorporating new sensor evolutions and exploring innovative approaches to improving performance in GPS degraded environments. Accelerating our time to delivery by leveling up our sensor fusion and calibration. This includes fusing multi-user, multi-session point cloud maps and automating alignment of LiDAR and imagery data to produce consistent large-scale scenes. Power scalability and reliability by eliminating the need for extrinsic measurements on our vehicle sensors in the field and improving our ability to catch and correct potential data quality issues at their source.

Requirements

5-10 years of experience in perception for robotics
Comfortable in a fast-pace and high-ownership environment. You’re excited to collaborate, but also comfortable developing your own opinions.
Proficient in C++ and Python
Extensive experience developing SLAM solutions, ideally involving ground-based LiDAR
Experience with extrinsic and intrinsic sensor calibration, including automated data-driven calibration

Nice To Haves

Prior experience with ultra-wide angle cameras is a nice-to-have

Responsibilities

Improving the quality and consistency of our product in an increasing breadth of operating conditions.
Lead SLAM development including incorporating new sensor evolutions and exploring innovative approaches to improving performance in GPS degraded environments.
Accelerating our time to delivery by leveling up our sensor fusion and calibration.
Fusing multi-user, multi-session point cloud maps and automating alignment of LiDAR and imagery data to produce consistent large-scale scenes.
Power scalability and reliability by eliminating the need for extrinsic measurements on our vehicle sensors in the field and improving our ability to catch and correct potential data quality issues at their source.