Senior Machine Learning Engineer, Perception and Controls

Capstan Medical is hiring a Senior Machine Learning Engineer to advance perception and controls for a heart valve robotic system with real-time, FDA design-controls documentation.

Responsibilities

• Develop registration methods to align intraprocedural imaging (fluoroscopy and echocardiography) to the robot.
• Estimate the pose of catheters and implants from medical images.
• Fuse image-based estimates with robot kinematics and additional sensing.
• Quantify uncertainty for each estimate.
• Build data pipelines for imaging and robot data, including capture, alignment, labeling, and dataset versioning for training and evaluation.
• Use simulation and synthetic data when clinical data is limited.
• Fit and improve models of device behavior from data, partnering with controls engineers to improve control performance.
• Work with clinical engineers and physicians to understand what images show, what matters in the procedure, and what accuracy is sufficient.
• Read relevant literature, prototype promising approaches, and report plainly what works and what does not on the team’s data.
• Deploy models to the robot while meeting real-time latency budgets.
• Write validation materials, test datasets, and design documentation needed for learned components to pass FDA design controls.

Requirements

• Education: MS in Computer Science, Electrical Engineering, Robotics, or a related field (PhD a plus).
• Experience: 4+ years of professional experience in computer vision or machine learning (classical or learned), including at least one production system shipped on real-world data.
• Experience working with scarce, noisy, or expensive data, using approaches such as synthetic data, augmentation, self-supervision, or physics priors.
• Experience building ML systems on data from physical systems such as robots, cameras, medical imaging, or sensors.
• Ability to thrive in a fast-paced environment and own problems end-to-end.
• Ability to work onsite 3–4 days per week, flexibly split between Santa Cruz, CA and West Menlo Park, CA offices, with at least 1 day per week in Santa Cruz.

Technologies

• Python, PyTorch, C++
• ROS, ROS2
• ONNX, TensorRT
• Kalman filters, factor graphs

Preferred Qualifications

• Ultrasound or echocardiography experience (strongly preferred). Fluoroscopy or X-ray experience is also valuable, including 2D/3D registration or digitally reconstructed radiographs.
• Experience tracking catheters, needles, surgical tools, or continuum robots in images.
• Sensor fusion and state estimation experience (e.g., Kalman filters or factor graphs).
• System identification or learned dynamics for control, including residual models on top of physics.
• Robotics software experience with ROS/ROS2 and on-device inference under latency constraints (ONNX, TensorRT).
• Data platform and MLOps experience, including dataset versioning and experiment tracking.
• Medical device or safety-critical background, including validating ML under FDA design controls.
• Experience as an early ML engineer on a team, setting up tools, data practices, and evaluation others build on.
• Publications at venues such as MICCAI, IPCAI, CVPR, ICRA, or IROS.

Workplace

• Type: Hybrid
• Onsite: 3–4 days per week across Santa Cruz and West Menlo Park, CA
• Requirement: at least 1 day per week in Santa Cruz

Reports to

• Robotics & Controls Manager

Benefits

• Outstanding benefits with medical, dental, and vision covered at 100% for you and your family, plus flex time off.
• Fun, fast-paced, collaborative environment working on transformational technologies in the cardiac healthcare space.
• Work-hard, play-hard environment with office outings.

AI Tools Notice

• Capstan Medical may use artificial intelligence (AI) tools during parts of the hiring process (e.g., reviewing applications, analyzing resumes, assessing responses, and identifying potential inconsistencies or verification signals).
• AI tools support the recruitment team but do not replace human judgment.
• Final hiring decisions are made by humans.