Sr. Robotics Engineer, Motion Planning

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

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!

Contoro 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.

We are looking for a Senior Robotics Engineer to lead the next phase of motion-performance improvement for our robot arm. You will be the technical lead for motion planning and trajectory generation, owning how we turn planned motion into fast, smooth, dynamically feasible trajectories under real hardware constraints. Your focus is reducing cycle time while maintaining safety and payload stability, using strong fundamentals in kinematics, dynamics, constrained optimization, and hardware-backed performance validation.

This is a senior individual-contributor role: you set technical direction for motion planning, own the hardest trajectory-optimization problems, and mentor other engineers, working closely with the autonomy team.

Trajectory Optimization

• Own trajectory generation and time parameterization: turn 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 the next generation of our 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 that maintains payload stability and hardware safety, and robustly handle 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., Move It, OMPL, CHOMP/Traj Opt), making the build, adopt, and extend decisions for the planning stack.

• Integrate perception outputs (container frame, box poses, occupancy) into the planning scene, reasoning about collision objects such as container walls, ceiling, and neighboring boxes.

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.

• Collaborate across autonomy, perception, controls, and robot software to deliver end-to-end motion that is both fast and reliable across diverse box configurations.

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…