Overview In this role you define the control architectures for contact-rich manipulation in production-scale robot workcells. You set the technical direction for how grasping systems operate, balancing speed, quality, and adaptability. You collaborate across teams to treat the platform as a cohesive system and design compliant end-effectors. You learn from field data to improve recovery from unexpected contact and drive the path from lab results to warehouse-scale performance. You mentor colleagues and establish scalable reference implementations and evaluation standards.
Compensation / Benefits- Medical, Dental, and Vision Coverage
- Maternity and Parental Leave Options
- Paid Time Off (PTO)
- 401(k) Plan
- Sign-on payments and RSUs
- Comprehensive benefits including health insurance and life/AD&D insurance
Responsibilities- Own the technical direction and contact-control strategy for contact-rich manipulation, balancing speed, performance, quality, cost, complexity, and adaptability.
- Identify open scientific problems at production scale and invent methods to solve them.
- Architect contact control with force and tactile sensing, including compliant behaviors and hybrid position/force control; contribute hands-on code.
- Collaborate with scientists, hardware designers, and systems engineers to treat arm and end-effector as a single system; co-design compliant end-effectors.
- Create mechanisms to learn from fielded production, analyze failure modes, and improve recovery from unexpected contact.
- Shape how simulation, analytical models, demonstrations, and real-robot data combine to scale lab results to warehouse performance.
- Define reference implementations, evaluation standards, and design-review practices to enable others to build on the architecture.
- Develop and mentor other scientists and engineers through technical reviews and hiring leadership.
Key requirements- PhD in Robotics, Machine Learning, Computer Science, Electrical Engineering, Mechanical Engineering, or related field, or equivalent body of published/deployed work
- Experience programming in Python and C++ with production-quality code on real robotic hardware
- Expertise in force, impedance, or admittance control for contact-rich manipulation
- Experience integrating learned policies with low-level force/impedance controllers and choosing action representations for contact-rich tasks
- Track record of setting technical direction adopted by an organization or research community
- distilling informal requirements into clear problem definitions
- working with ambiguity and competing objectives
- technical leadership and mentorship
- force/impedance/admittance control
- learned policy integration with low-level controllers
- simulation and real-robot data fusion
