Reports to: Manager of Robotics and Controls
Workplace Type: Hybrid (onsite average of 3 days/week in Santa Cruz and the
new Bay Area office near West Menlo Park).
At Capstan Medical, we’re building one of the most exciting and innovative companies in medtech—developing a first-of-its-kind robotic platform for minimally invasive heart valve treatment. Our team combines surgical robotics, catheter-based delivery, and next-generation implants to transform complex procedures into safer, lower-stress solutions for patients and clinicians alike. As a highly collaborative, hands-on team, we move fast, wear multiple hats, and believe the best ideas can come from anyone.
Based in Santa Cruz, our unique workspace blends cutting-edge Bay Area innovation with a lifestyle-driven environment near trails, beaches, and open space—creating the perfect place to do meaningful, career-defining work.
What You’ll Do:
Design, implement, and verify robotic control algorithms for Capstan's
catheter-based surgical platform — kinematics, dynamics, teleoperation,
and motion control.
Develop forward and inverse kinematic models for continuum and tendon-
driven mechanisms, and validate them against real-world data.
Build trajectory engines, drive modes, and constraint-aware motion
algorithms that translate surgeon intent into safe, precise catheter motion.
Design and execute characterization studies on actuators, tendon
transmissions, and full system performance; translate experimental results
into models, parameters, and acceptance criteria.
Define algorithm-level performance specifications and hazard-driven fault
detection thresholds; partner with Systems and Quality to support design
verification and regulatory submissions
Translate clinical and user needs into design requirements, prototype
rapidly on real hardware, and carry features through verification to
product launch
Drive technical direction for path planning, catheter control, or robotics
algorithms across multiple hardware programs (increased level of
architectural ownership and cross-program scope for Staff)
Mentor engineers on the team, lead design reviews, and contribute to
hiring and onboarding (increased level of mentorship for Staff)
Document your work through design reviews and released DHF
documentation, and identify gaps and pitch in as needed to keep the team
moving
Strongly Preferred:
Strong foundation in robot kinematics and dynamics - forward/inverse kinematics, Jacobians, rigid-body dynamics, and ideally continuum, concentric tube, or tendon-driven systems
Fluent with classical and modern control -- PID, feedforward, model-based, optimal/MPC, impedance/admittance -- and the judgment to know when each is appropriate
Hands-on experience implementing control algorithms in modern C++ (14/17/20) for real-time, safety-critical systems, with Python for rapid prototyping, data analysis, and tooling
Motion planning and trajectory generation experience — constrained nonlinear optimization, collision-aware planning, or task-space control paradigms
State estimation and sensor fusion experience — Kalman/EKF/UKF, particle filters, or nonlinear observers, with a working understanding of noise models and sensor calibration
Comfortable characterizing real electromechanical systems on the bench; you can design the experiment, run it, analyze the data, and turn it into a model.
Close-to-hardware sensibility: encoders, motor controllers, force sensors, brakes, IMUs -- you understand the gap between textbook systems and real ones
Strong object-oriented design instincts, with the discipline to factor algorithm code so it can be unit-tested, reviewed, and maintained as the team scales
Medical robotics or safety-critical systems background -- you know why "it works in sim" or "it works most of the time" isn't good enough
Understanding of how early design decisions cascade into downstream cost; ability to make smart calls on clinical workflow, regulation, and risk management to save time and effort later
Requirements:
BS/MS in Robotics, Mechanical Engineering, Electrical Engineering, Computer Science, or equivalent; MS or PhD preferred
5+ years (Senior) or 8+ years (Staff) of hands-on robotics or controls development; PhD with directly relevant research or projects can offset some industry experience
Track record of shipping robotic control algorithms in real production systems, ideally end-to-end from concept to production, IDE/clinical use, or FDA-cleared product
Experience navigating ambiguity in early- and mid-stage development while delivering concrete, testable results
Experience with medical device development process — design control, risk management, design verification — or equivalent experience in another safety-critical regulated domain
Demonstrated ability to derive math from first principles and implement it in working code; we want the whiteboard and the IDE in the same person
Strong written and verbal communication, meaning that you can write a clear design doc, defend a design review, and explain a controller to a non-controls engineer
Comfortable working hands-on in a lab environment alongside hardware, benchtop fixtures, animals (preclinical), and clinicians
Ability to work in a hybrid work environment, working onsite an average of 3 days a week, in a mix of our Santa Cruz HQ and our new Bay Area office near West Menlo Park.
Bonus
Flexible robotics experience -- concentric tube robots, tendon-driven, soft, or other compliant manipulators
Surgical robotics or another regulated, safety-critical robotics background
Sensing, electromagnetic tracking, or other catheter-tip localization experience
Experience integrating fluoroscopy, ultrasound, or CT imaging into robotic guidance, registration, or visual servoing
ROS1 or ROS2 experience in production systems, with an understanding of its real-time tradeoffs
Working knowledge of regulatory standards (FDA, IEC 62304, ISO 14971, IEC 60601) and how they shape algorithm and architecture decisions
Experience with simulation environments (Drake, MuJoCo, Isaac Sim, or custom) for development, regression, and verification
Familiarity with QNX or real-time Linux: you don't have to own the stack, but you should understand the constraints it places on your algorithms
Track record of technical leadership and mentorship at a comparable medical robotics or capital equipment company
