Cardiovascular disease is the #1 cause of morbidity and mortality in the world. Much of this could be prevented with better access to specialist care. Take stroke as an example: any delay in treatment can lead to permanent disability or death. However, due to a lack of specialist surgeons, the most effective intervention can only be performed in 2% of US hospitals. For patients who present to one of the 98% of hospitals that do not offer the surgery, treatment is either significantly delayed or not offered at all because timely transfer is not feasible.
Our mission is to bring state-of-the-art vascular intervention to anyone, anytime, regardless of their location. Our team of medical clinicians, roboticists, and machine learning experts are working to bridge this gap by building the world’s first remotely-operated, semi-autonomous endovascular surgical robot.
We’ve already done what nobody else could—using our system, doctors from around the world were able to remotely perform this procedure from as far as 8000 miles away. We have now successfully performed first-in-human cases, including a remotely operated procedure, demonstrating the potential of our technology to revolutionize access to life-saving interventions. We now need your help to bring this technology out of the laboratory and into hospitals everywhere.
The RoleWe’re looking for someone to continue leveraging our vast trove of medical imaging data in order to train and deploy deep neural network models. These models enable our surgical robot to understand and reason about both our robot and the patient’s anatomy, which ultimately gives doctors the insight and control necessary to quickly and safely complete the procedure.
You HaveAt least 2 years of machine learning engineering experience (level will be commensurate with your experience)
Experience developing high-quality software, ranging from design and implementation to testing and deployment
Expertise with Python
Experience training image-based deep neural networks, including
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
Eagerness to learn on the job, iterate fast, and collaborate
Experience developing and deploying neural networks for physical systems, such as robots and autonomous vehicles
Experience with medical imaging data such as x-rays, CTs, and MRIs
Experience bridging the sim-to-real gap
Top Skills
What We Do
Remedy Robotics exists to bring flawless, immediate, endovascular intervention (EI)—treatment for stroke, heart attack, bleeding, aneurysmal disease, pulmonary embolism and more— to every patient worldwide. Remedy is the only company in the world to have performed:
- Completely robotic neurointerventional procedures in humans from start to finish.
- Completely remote robotic neurointerventional procedures in humans from from start to finish.
- Autonomous endovascular navigation.
A few key principles underlie our work. We strongly believe that:
- EI is optimizable. Tool movements should be deliberate and efficient. Procedures should be fast and effective. Complications should be avoided without exception.
- All patients at elite US institutions deserve access to flawless EI without delay. But so do all patients at smaller US community hospitals. And so do all patients in Kinshasa and Port Moresby and Alice Springs and anywhere in the world.
- The world's finest technology and technologists should focus on advancing our health and wellbeing. They belong at Remedy Robotics.
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