Remedy Robotics

Medical

MachineLearningEngineer

San Francisco, California, United States; New York, New York, United States FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid+ candidates.

The Brief

“Machine Learning Engineer at Remedy Robotics. Skills: Machine learning, Robotics, Deep learning, Simulation, Medical imaging, Autonomy. Work across the full stack of autonomy—from perception and scene understanding to planning, control, and deployment on real robotic systems. Leverage large-scale simulated and real-world datasets to train and evaluate deep learning models”

What You'll Achieve.

Building autonomous systems capable of delivering life-saving interventions when and where human specialists are unavailable

Industry & Context.

Medical
Problems you'll solve

Hard, open-ended technical problems

What They're Looking For.

Must Have

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, 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 - software, such as ROS, Experience with robotics - algorithms, such as motion planning, Experience with robotics - math, such as transforms, Experience with simulators, such as MuJoCo or Isaac, Experience developing high-quality software, ranging from design and implementation to testing and deployment

Nice to Have

Experience with medical imaging data such as x-rays, CTs, and MRIs, Experience bridging the sim-to-real gap, Experience with reinforcement learning

What You'll Do.

Work across the full stack of autonomy—from perception and scene understanding to planning

and deployment on real robotic systems

Leverage large-scale simulated and real-world datasets to train and evaluate deep learning models

Enable robots to understand anatomy

reason about intervention strategies

and safely operate in highly constrained environments

and deploy new capabilities

How You'll Work.

Team & Collaboration

Collaborate closely with roboticists, machine learning engineers, clinicians, and hardware teams

Full Job Description

ABOUT REMEDY ROBOTICS 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 ROLE We’re looking for an interdisciplinary engineer who 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’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 t

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