Location: Austin, TX
Salary: $150,000.00 USD Annually - $180,000.00 USD Annually
Senior Robotics Engineer - Motion Planning
Location: Austin, TX (Onsite)
Job Type: Full-Time
We are seeking a Senior Robotics Engineer, Motion Planning to lead the next phase of motion-performance improvement for advanced robotic manipulation systems used in warehouse automation. This role is focused on developing fast, smooth, and dynamically feasible robot motion under real-world hardware constraints. You will serve as the technical leader for motion planning and trajectory generation, driving throughput improvements while maintaining safety, reliability, and payload stability. This is a senior individual contributor position requiring deep expertise in robotic manipulation, trajectory optimization, motion planning, and real-world robotic deployments.
Responsibilities
- Own trajectory generation and time parameterization, converting planned paths into time-optimal, dynamically feasible trajectories.
- Minimize cycle times while respecting velocity, acceleration, jerk, torque, and payload constraints.
- Drive performance improvements through advanced time parameterization techniques and optimization-based motion planning approaches, including optimal control and QP/NLP-based methods.
- Develop smooth, jerk-limited motion profiles that maximize hardware safety and payload stability.
- Address kinematic edge cases such as singularities and joint-limit constraints.
Path Planning and Motion Architecture
- Lead geometric path planning for high-degree-of-freedom robotic manipulators operating in complex and cluttered environments.
- Evaluate, architect, and improve motion-planning frameworks and toolchains, including technologies such as MoveIt, OMPL, CHOMP, and TrajOpt.
- Integrate perception outputs into planning environments for collision-aware motion execution.
- Ensure robust collision avoidance around structures, obstacles, and neighboring objects.
Performance Validation
- Define and track key motion-performance metrics.
- Benchmark alternative planning approaches and validate performance gains in simulation and on physical robotic systems.
- Utilize physics-based and kinematic simulation environments to de-risk deployments and improve system reliability.
Technical Leadership
- Establish technical direction for motion-planning initiatives.
- Drive long-term improvements in cycle time, throughput, and operational reliability.
- Mentor and support junior and mid-level engineers.
- Collaborate closely with autonomy, perception, controls, and software engineering teams to deliver high-performing robotic solutions.
Minimum Qualifications
Experience
- 5+ years of professional experience in:
- Motion planning
- Trajectory optimization
- Robotic manipulator control
- Demonstrated experience deploying robotic systems on real hardware.
- Proven ownership of motion-planning performance and system optimization.
Education
- Bachelor's or Master's degree in:
- Robotics
- Computer Science
- Mechanical Engineering
- Electrical Engineering
- Related technical field
- Equivalent practical experience will also be considered.
Technical Skills
- Strong expertise in classical trajectory generation and time-parameterization methods, including:
- TOTG/TOPP-RA
- Ruckig
- S-curve motion profiles
- Deep understanding of manipulator kinematics and dynamics, including:
- Forward and inverse kinematics
- Collision checking
- Velocity, acceleration, jerk, and torque constraints
- Singularity handling
- Joint-limit management
- Experience with optimization-based motion planning approaches such as:
- Optimal control
- Quadratic programming (QP)
- Nonlinear programming (NLP)
- Strong proficiency in:
- Modern C++
- Python
- ROS1 and/or ROS2
- Experience validating performance improvements through simulation and real-world testing.
Soft Skills
- Strong analytical and problem-solving abilities.
- Ability to lead complex technical initiatives with minimal direction.
- Excellent communication and cross-functional collaboration skills.
- Experience mentoring and developing engineers.
Preferred Qualifications
- Experience with MoveIt and related planning frameworks.
- Knowledge of motion-planning algorithms including:
- RRT
- RRT-Connect
- PRM
- CHOMP
- TrajOpt
- Experience working with industrial robotic manipulators and real-time control systems.
- Experience with multi-object or multi-pick manipulation planning.
- Background optimizing throughput and cycle time in production robotics environments.
- Experience with GPU-accelerated or learning-based motion-planning techniques.
- Experience using simulation platforms such as:
- Isaac Sim
- Gazebo
- MuJoCo
- Bullet
Work Environment
- Location: Austin, Texas
- Work Arrangement: Fully onsite
- Collaborate closely with multidisciplinary teams in a fast-paced engineering environment focused on robotics innovation and real-world deployment.