Perception And Controls Data Jobs

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Senior Machine Learning Engineer, Perception and Controls

Capstan Medical, Inc. West Menlo Park, CA

West Menlo Park, CA

Today

Full time Artificial Intelligence Computer Vision Data Analysis

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Job Description

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.

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