Senior / Staff Robotics Engineer, Manipulation

Responsibilities

• Advanced Motion Planning & Trajectory Generation: You will architect the algorithms that drive high-DOF arm motion in dynamic environments. This involves implementing constrained motion planners that generate smooth, jerk-limited trajectories in real-time. You will also solve the "Whole Body" control problem, coordinating the mobile base and the manipulator arm simultaneously to extend the robot's workspace and maintain stability during heavy lifting tasks.
• Interaction Control & Compliance: You will develop the low-level control strategies that enable the robot to physically interact with the world safely. This includes designing and tuning impedance/admittance controllers that allow the robot to modulate stiffness based on force feedback-essential for tasks like opening heavy doors or plugging in connectors.
• Teleoperation & Human-Robot Interface: You will build the mathematical engine behind our remote manipulation capabilities. You are responsible for the logic that translates human operator inputs into feasible, safe robot motions. You will design the control mapping and assistance layers that ensure remote manipulation feels intuitive and stable, managing the complex translation between human intent and the robot's physical constraints without compromising safety.

Requirements

• Experience: Ph.D. in Robotics, Mechanical Engineering, Computer Science, or related field, OR an M.S. degree with 4+ years of relevant industry experience.
• Applied Mathematics: Deep understanding of rigid body kinematics, dynamics, and 3D geometry. You are fluent in linear algebra and Lie theory for representing robot state.
• Modern C++ Expertise: You write production-grade, real-time C++. You are comfortable with modern standards (C++17/20) and libraries like Eigen, KDL, or Pinocchio.
• Planning Frameworks: Experience with motion planning libraries (e.g., OMPL, MoveIt, TrajOpt, or similar).
• Control Theory: Practical experience implementing PID, Impedance Control, or Model Predictive Control (MPC) on real hardware.
• Requires 5 days/week in-office collaboration with the teams.

Bonus Qualifications

• Physics Simulation: Experience tuning physics parameters in simulators like Isaac Sim, MuJoCo, or Gazebo to match real-world dynamics.
• Optimization: Familiarity with solvers like OSQP, Ipopt, or Ceres for trajectory optimization.
• ML for Control: Interest or experience in Reinforcement Learning (RL) or Learning from Demonstration (LfD) for manipulation tasks.
• Real Actuators: Experience working with industrial communication buses (EtherCAT/CAN) and motor drives.

Benefits

• Competitive stock options/equity programs.
• Health, dental, and vision insurance, 401(k) plan.
• Visa sponsorship and green card support for qualified candidates.
• Lunches and dinners, a fully stocked kitchen, and regular team-building events.

Compensation

Salary $160,000-$265,000 USD + Bonus + Equity

The base salary range above represents the expected compensation for this full-time U.S. position. Final compensation will be determined based on role scope, level, location, job-related skills, experience, and relevant education or training, and may fall outside the listed range in exceptional cases.