Sr. Robotics Engineer, Motion Planning

Senior Robotics Engineer, Motion Planning

Join Contoro Robotics – Revolutionizing Warehouse Automation with Cutting-Edge Robotics

• Responsibilities:
• Trajectory Optimization: Own trajectory generation and time parameterization, turning planned paths into time-optimal, dynamically feasible trajectories that minimize cycle time while respecting velocity, acceleration, jerk, and torque limits of the arm and payload.
• Drive Next Generation Motion Performance: Through advanced time parameterization, optimization-based motion (optimal control, QP/NLP), and payload-aware planning that meaningfully increases throughput.
• Ensure Smooth, Jerk-Limited Motion: Maintaining payload stability and hardware safety, and robustly handling near-singularity and joint-limit edge cases without stalls or unsafe motion.
• Path Generation and Planning Architecture: Own geometric path planning for a high-DOF manipulator moving boxes through cluttered, partially occluded container environments. Evaluate and evolve the planning architecture and toolchain (e.g., MoveIt, OMPL, CHOMP/TrajOpt).
• Integrate Perception Outputs: Reasoning about collision objects such as container walls, ceiling, and neighboring boxes, integrating perception outputs (container frame, box poses, occupancy).
• Performance Validation: Define motion-performance metrics, benchmark alternative approaches, and validate gains both in simulation and on real hardware. Use physics-based and kinematic simulation to develop and de-risk changes before they reach the fleet.
• Technical Leadership: Set technical direction for motion planning and drive multi-quarter improvements in cycle time and reliability. Mentor junior and mid-level engineers and raise the team's bar on motion-planning craft, testing, and reliability.
• Collaboration: Collaborate across autonomy, perception, controls, and robot software to deliver end-to-end motion that is both fast and reliable across diverse box configurations.

• Qualifications:
• Experience: 5+ years of professional experience in motion planning, trajectory optimization, or manipulator control, with production or real-hardware deployment and a track record of owning motion performance end-to-end.
• Education: B.S. or M.S. in Robotics, Computer Science, Mechanical/Electrical Engineering, or a related field (or equivalent industry experience).
• Technical Skills: Strong grounding in classical trajectory generation and time-parameterization methods (e.g., TOTG/TOPP-RA, Ruckig, S-curve profiles), with the ability to derive, adapt, and implement them in production systems. Deep grasp of manipulator kinematics and dynamics - forward/inverse kinematics, collision checking, velocity/acceleration/jerk and torque constraints, and singularity and joint-limit handling for 6/7-DOF arms. Background in optimization-based motion (optimal control, QP/NLP-based trajectory optimization). Deep proficiency in C++ (modern standards), Python, and ROS 1 or ROS 2. Experience validating cycle-time and reliability improvements on real hardware, backed by simulation.
• Soft Skills: Strong problem-solving and data-driven decision-making; able to own ambiguous, high-impact problems and decompose them into actionable work. Excellent communication - able to present complex technical concepts clearly to cross-functional teams and mentor other engineers.
• Nice to Have: Hands-on expertise with MoveIt and motion planning frameworks (OMPL, RRT/RRT-Connect/PRM, CHOMP/TrajOpt). Experience with industrial manipulators (e.g., KUKA) and real-time joint control. Experience planning for multi-object or multi-pick manipulation. Experience optimizing for throughput or cycle time in a production robotics or logistics setting. Experience with GPU-accelerated or learning-based motion planning in addition to classical methods. Experience with physics-based or kinematic simulation for planning validation (Isaac Sim, Gazebo, MuJoCo, Bullet).