Robotics Engineer, Autonomy
Contoro Inc.3 months ago
Responsibilities
- Advance motion planning modules including grasp planning, trajectory generation, and collision avoidance.
- Contribute to the behavior tree governing autonomous unloading, including pick selection, drop verification, and error recovery.
- Improve pick success rates and cycle time through software changes.
- Debug and resolve production issues using remote log analysis and telemetry.
- Write and maintain automated tests for motion planning and behavior logic.
- Collaborate with perception, hardware, trajectory optimization, and operations engineers on cross-system integration.
- Participate in design reviews and contribute to module-level technical decisions.
Requirements
- Bachelor’s or master’s degree in Robotics, Computer Science, Mechanical Engineering, or a related field.
- 3+ years of professional experience developing software for deployed robotic systems.
- Proficiency in C++ and Python in production robotics environments.
- Experience with ROS and motion planning frameworks such as MoveIt.
- Working knowledge of kinematics, inverse kinematics, and manipulator collision avoidance.
- Experience with behavior trees or state machines for robot autonomy.
- Strong debugging skills and ability to diagnose production-system issues.
- Familiarity with Linux-based development environments.
- Preferred: experience with industrial manipulators such as KUKA, ABB, Fanuc, or UR.
- Preferred: familiarity with grasp planning, manipulation under occlusion, and occupancy mapping for collision avoidance.
- Preferred: experience with Docker-based deployment and cloud-based logging or monitoring.
- Preferred: prior work in warehouse automation, surgical robotics, logistics, or pick-and-place applications.
About Contoro Inc.
Contoro Robotics is an Austin-based robotics startup that is revolutionizing industrial automation with AI-powered robots, focused on automating the unloading of floor-loaded trailer and shipping containers from trucks. Their pioneering human-in-the-loop (HITL) model ensures over 99% success in real-world applications, bridging the gap between AI limitations and the commercial viability of advanced robotics solutions.