Staff Robotics Engineer, Manipulation

What you will do

• Set the manipulation architecture and technical direction across task planning, sensing, learned-policy integration, contact reasoning, monitoring, recovery, and execution.
• Design manipulation behaviors for contact-rich tasks, including contact selection, constrained motion, force regulation, and recovery.
• Integrate and evaluate learned manipulation policies, including vision-language-action models and other embodied foundation models, through the full sensing, control, monitoring, and recovery stack.
• Implement production-quality planning and execution software in C++ and Python for real-time operation on insectoids.
• Lead cross-stack design reviews and resolve tradeoffs spanning sensing, control, actuation, operator interfaces, and mechanical constraints.
• Build task-level monitors that detect loss of contact, geometric mismatch, saturation, obstruction, and unsuccessful execution.
• Define hardware experiments, metrics, and regression tests for completion rate, cycle time, force accuracy, recovery rate, and failure mode.
• Analyze unsuccessful trials and convert the dominant causes into algorithm, sensing, controller, or mechanical changes that survive repeated physical test.

Minimum qualifications

• Bachelor's degree in robotics, mechanical engineering, electrical engineering, computer science, or a related field, or equivalent practical experience.
• Demonstrated ownership of architecture and technical direction for a deployed manipulation system spanning planning, sensing, control, monitoring, and recovery.
• Strong C++ and Python skills, including experience with a robotics framework such as ROS 2, Drake, MoveIt, Pinocchio, or an equivalent internal stack.
• Built and deployed a closed-loop manipulation capability on a physical robot; you can explain its architecture and provide measured results from repeated trials.
• Led a failure-driven redesign that separated planning, perception, control, and hardware causes and produced a correction that survived repeated physical test.

Preferred experience

Compensation

• The annual base salary range for this San Francisco position is $200,000–$260,000. An offer within this range will reflect the position's approved scope and the candidate's demonstrated role-relevant skills and experience.

Working at GRAM

Interview Process

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