Autonomy Engineer

About Remedy Robotics

Remedy Robotics is a medical technology company developing robotic systems for endovascular intervention. Its proprietary technology combines robotics, machine learning, and advanced computer vision to help physicians perform highly precise endovascular procedures and expand access to life-saving stroke and cardiovascular care. Initially focused on neurovascular intervention, Remedy is addressing the limited availability of specialized treatment for time-critical cardiovascular emergencies, with the long-term goal of enabling expert intervention regardless of patient location. Headquartered in San Francisco, Remedy is backed by DCVC, Blackbird, and Tony Fadell's Build Collective, among others.

The Role

We’re looking for an interdisciplinary engineer and researcher to lead the development of autonomy and intelligence for the DARPA MASH (Medics Autonomously Stopping Hemorrhage) program. The goal of MASH is to enable autonomous robotic systems to rapidly control internal bleeding in environments where immediate access to expert surgical care is impossible.

This role sits at the intersection of robotics, machine learning, simulation, and medical imaging. You will work across the full stack of autonomy—from perception and scene understanding to planning, control, and deployment on real robotic systems. You will leverage large-scale datasets to train and evaluate deep learning models that enable robots to understand anatomy, reason about intervention strategies, and safely operate a robot in highly constrained human vasculatures. This role is primarily focused on machine learning, but is interdisciplinary and will also involve simulation, medical imaging, and robotics.

You will collaborate closely with other machine learning engineers, roboticists, and clinicians to rapidly prototype, test, and deploy. The ideal candidate is excited by challenging, open-ended technical problems and highly motivated by our ultimate mission: to save lives.

You Have

• One ofBachelor’s degree with 4+ years of relevant industry experienceMaster’s degree with 2+ years of relevant industry experiencePhD and 0+ years of industry experience
• Expertise with Python
• Experience training image-based deep neural networks, includingDeep neural network libraries such as PyTorchDefining training and validation datasetsUsing data augmentations during trainingSelecting loss functions and metricsCloud-based data and trainingConducting large-scale experiments to determine actionable improvements
• Experience with simulators, such as MuJoCo or Isaac
• Experience developing high-quality software, ranging from design and implementation to testing and deployment
• Eagerness to learn on the job, iterate fast, and collaborate

Nice to Haves

• Experience with roboticssoftware, such as ROS2algorithms, such as motion planningmath, such as transforms
• Experience with medical imaging data such as x-rays, CTs, and MRIs
• Experience bridging the sim-to-real gap

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