The Machine Learning Engineer will join Remedy Robotics in San Francisco, CA (onsite), contributing to autonomous systems from perception to deployment at the intersection of robotics, machine learning, simulation, and medical imaging.
Responsibilities
- You will work across the full stack of autonomy—from perception and scene understanding to planning, control, and deployment on real robotic systems.
- You’ll leverage large-scale simulated and real-world datasets to train and evaluate deep learning models that enable robots to understand anatomy, reason about intervention strategies, and safely operate in highly constrained environments.
- You will collaborate closely with roboticists, machine learning engineers, clinicians, and hardware teams to rapidly prototype, test, and deploy new capabilities.
- Your work will directly contribute to building autonomous systems capable of delivering life-saving interventions when and where human specialists are unavailable.
Requirements
- Bachelor’s degree and 4+ years experience
- Master’s degree and 2+ years experience
- PhD and 0+ years experience
- Expertise with Python
- Experience training image-based deep neural networks
- Deep neural network libraries such as PyTorch
- Defining training and validation datasets
- Using data augmentations during training
- Selecting loss functions and metrics
- Cloud-based data and training
- Conducting large-scale experiments to determine actionable improvements
- Experience with robotics
- ROS
- motion planning
- transforms
- 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
Technologies
- Python
- PyTorch
- ROS
- MuJoCo
- Isaac
About Remedy Robotics
Cardiovascular disease is the leading cause of morbidity and mortality worldwide, and timely access to specialist care can markedly influence outcomes. For conditions like stroke, delays in treatment can lead to permanent disability or death. Yet many hospitals lack access to trained interventionists, resulting in postponed or unavailable care. Remedy Robotics aims to democratize state-of-the-art vascular intervention by delivering a remotely operated, semi-autonomous endovascular surgical robot that can be used anywhere, at any time.
The company brings together medical clinicians, roboticists, and machine learning experts to close this gap and advance remote surgical capabilities. Remedy Robotics has demonstrated remote procedures across vast distances, including doctors performing procedures from up to 8000 miles away, and has completed first-in-human cases to show feasibility and safety. The team seeks to move this technology from the laboratory into hospitals worldwide to broaden access to life-saving interventions.
