Machine Learning Engineer

An interdisciplinary role at the crossroads of robotics, machine learning, simulation, and medical imaging, delivering autonomous systems from perception to deployment in collaboration with clinicians and hardware teams.

Responsibilities

• Contribute across the full autonomy stack, from perception and scene understanding to planning, control, and real-world deployment on robotic systems.
• Train and evaluate deep learning models using large scale simulated and real world datasets to enable anatomy understanding, intervention reasoning, and safe operation in highly constrained environments.
• Partner with roboticists, machine learning engineers, clinicians, and hardware teams to rapidly prototype, test, and deploy new capabilities.
• Contribute to autonomous systems capable of delivering life saving interventions when human specialists are unavailable.

Requirements

• Bachelor’s degree with 4+ years of experience; OR Master’s degree with 2+ years; OR PhD with 0+ years of experience.
• Strong proficiency in Python.
• Experience training image based deep neural networks.
• Experience with deep neural network libraries such as PyTorch.
• Experience defining training and validation datasets.
• Experience applying data augmentations during training.
• Experience selecting loss functions and metrics.
• Familiarity with cloud based data and training workflows.
• Ability to conduct large scale experiments to identify actionable improvements.
• Experience working in robotics, including ROS, motion planning, and transforms.
• Experience with simulators such as MuJoCo or Isaac.
• Track record developing high quality software from design through testing and deployment.
• Eagerness to learn on the job, iterate quickly, and collaborate across teams.

Technologies

• Python
• PyTorch
• ROS
• MuJoCo
• Isaac

About Remedy Robotics

Cardiovascular disease remains the leading cause of global morbidity and mortality, with access to specialist care uneven across regions. Stroke treatment is time sensitive, and delays can cause lasting disability or death. Our mission is to bring state of the art vascular intervention to everyone, anywhere, by building a remotely operated, semi autonomous endovascular surgical robot. The team combines medical clinicians, roboticists, and machine learning experts to close gaps in access to care. To date, doctors have remotely performed procedures across thousands of miles, with first in human cases demonstrating the potential to transform access to life saving interventions. We are expanding to bring this technology from the lab into hospitals worldwide.