At Contoro Robotics, we're on a mission to solve labor challenges through advanced robotic solutions. Headquartered in Austin, TX, our fast-growing startup is transforming the supply chain industry with our flagship warehouse automation technology. Our team is made up of top-tier experts in robotics, AI, and logistics, working together to push the boundaries of automation.
We’re looking for talented and ambitious individuals to join us on this journey—helping shape the future of robotics while growing alongside a world-class team. If you're passionate about innovation, problem-solving, and making a real-world impact, we want to hear from you!
Robotics Engineer, Motion PlanningContoro Robotics is an Austin-based company building autonomous truck-unloading robots for warehouse operations. We deploy reliable, high-throughput robotic systems that handle heavy, unstructured freight in real logistics settings every day.
The RoleWe are looking for a Robotics Engineer to help improve the reliability and performance of our robot's motion-planning stack on a live production fleet. A significant part of this role is hands-on production support: reproducing field issues, debugging them across motion planning, perception, and controls, and validating fixes on real hardware. You will work closely with our senior motion-planning and autonomy engineers, tuning and integrating motion planning as you grow your depth in the field.
ResponsibilitiesProduction Debugging and Performance Support
Investigate and help resolve production issues that affect cycle time, pick success, and operator intervention rate, working across motion planning, perception, and controls to find root cause.
Reproduce field failures on real hardware, analyze logs and telemetry, and work with senior engineers to validate root cause and ship fixes.
Motion Planning Implementation and Integration
Implement and tune planners within the MoveIt ecosystem for collision-free, kinematically feasible motion, with guidance from senior engineers.
Integrate perception outputs (container frame, box poses, occupancy) into the planning scene, reasoning about collision objects such as container walls, ceiling, and neighboring boxes.
Integrate path and trajectory generation with the control stack (MoveIt and ros_control), and measure cycle-time and throughput impact on hardware.
Hardware Validation
Run controlled tests on the robot, compare before-and-after throughput, and quantify the impact of changes across diverse box and container configurations.
Collaborate across autonomy, perception, controls, and robot software to deliver reliable end-to-end motion.
Experience: 1-3 years of professional experience (or equivalent research or internship experience) in motion planning, manipulator control, or robotics software, ideally with real-hardware exposure. Strong recent graduates with excellent fundamentals are encouraged to apply.
Education: Minimum B.S. in Robotics, Computer Science, Mechanical/Electrical Engineering, or a related field.
Technical Skills:
Proficient in C++ (modern standards), Python, and ROS 1 or ROS 2.
Working knowledge of MoveIt and at least one motion planning approach (e.g., sampling-based planners such as RRT/RRT-Connect/PRM, or optimization-based planners such as CHOMP/TrajOpt).
Solid grasp of manipulator kinematics - forward/inverse kinematics, collision checking, velocity and acceleration limits, and singularity and joint-limit awareness for 6/7-DOF arms.
Strong debugging instincts and a willingness to dig into hard, ambiguous production issues.
Good communication and eagerness to learn from senior engineers.
Hands-on experience with industrial manipulators (e.g., UR, KUKA) and real-time joint control.
Familiarity with integrating perception inputs (point clouds, object poses, occupancy maps) into collision-aware planning.
Exposure to time-parameterization tools (TOTG/TOPP-RA, Ruckig, jerk-limited/S-curve profiles).
A controls or electrical background (motor limits, torque, current) useful for hardware-level debugging.
Exposure to physics-based or kinematic simulation (Isaac Sim, Gazebo, MuJoCo, Bullet).
Skills Required
- 3+ years professional experience in motion planning, trajectory optimization, or manipulator control with production or real-hardware deployment
- B.S. in Robotics, Computer Science, Mechanical/Electrical Engineering, or related field (or equivalent industry experience)
- Proficient in modern C++ and Python
- Experience with ROS1 and ROS2
- Hands-on with MoveIt and motion planning frameworks (OMPL, sampling-based planners such as RRT/RRT-Connect/PRM, and/or CHOMP/TrajOpt)
- Experience with time-optimal trajectory generation/time parameterization (e.g., TOTG/TOPP-RA, Ruckig, jerk-limited/S-curve profiles)
- Strong grasp of manipulator kinematics and dynamics, collision checking, singularity and joint-limit handling for 6/7-DOF arms
- Experience integrating perception outputs (point clouds, object poses, occupancy maps) into collision-aware planning and validating cycle-time improvements on hardware
- Experience integrating path and trajectory generation with control stack (MoveIt / ros_control) and validating on real hardware
- Strong problem-solving skills and clear technical communication with cross-functional teams
- Experience with industrial manipulators (e.g., KUKA) and real-time joint control
- Background in optimization-based motion (optimal control, QP/NLP-based trajectory optimization)
- Experience planning for multi-object or multi-pick manipulation
- Experience optimizing throughput/cycle-time in production robotics or logistics settings
- Exposure to physics-based or kinematic simulation for planning validation (Isaac Sim, Gazebo, MuJoCo, Bullet)
What We Do
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.
