About the job
We are looking for a highly skilled and innovative Senior Machine Learning Engineer to apply the latest advances in learning-based manipulation to improve the performance and safety of surgical robotics. In this hands-on role you will rapidly design models, implement algorithms, and bring ML-trained manipulation behaviors from research to real-world robotic hardware in unstructured environments. As a senior member of the team, you will be responsible for mentoring engineers and elevating the team's overall technical capabilities.
Responsibilities
Developing and implementing ML algorithms for surgical robotic task automation.
Building pipelines for data collection, training, testing and deployment of ML models.
Leverage simulation for prototyping, training, and transfer to robot hardware.
Define and evaluate performance metrics for surgical tasks and implement rigorous testing protocols.
Collaborate with software and controls teams to deploy learned policies and ensure safe and reliable execution.
Optimize models for onboard real-time performance on robotic hardware.
Stay current with the latest robotics and AI research, mentor team members, and drive innovation.
Qualifications
Minimum
PhD/MS in Machine Learning, Computer Science, Robotics, or related field and 0+/3+ years of work experience.
3+ years of hands-on experience implementing and deploying ML models for robotic manipulation and experience with large multimodal ML models.
Mastery of Python for prototyping and experience in C++ for deployment on robotic hardware.
Strong proficiency in deep learning frameworks (e.g., PyTorch, TensorFlow).
Experience optimizing ML models for real-time performance on robotic hardware.
Strong experience with simulation platforms (e.g., MuJoCo, Isaac Sim) and sim-to-real transfer.
Understanding of robot kinematics, dynamics, sensing, and control.
Preferred
Familiarity with build tools and version control systems.
Exposure to agile development processes, CI/CD, and issue tracking tools.