Machine Learning Intern

Company Description

It started with a simple idea: what if surgery could be less invasive and recovery less painful? Nearly 30 years later, that question still fuels everything we do at Intuitive
. As a global leader in robotic-assisted surgery and minimally invasive care
, our technologies—like the da Vinci surgical system and Ion
—have transformed how care is delivered for millions of patients worldwide.

We’re a team of engineers, clinicians, and innovators united by one purpose: to make surgery smarter, safer, and more human. Every day, our work helps care teams perform with greater precision and patients recover faster, improving outcomes around the world.

The problems we solve demand creativity, rigor, and collaboration. The work is challenging, but deeply meaningful—because every improvement we make has the potential to change a life.

If you’re ready to contribute to something larger than yourself and help transform the future of healthcare, you’ll find your purpose here.

Primary Function of Position

Are you passionate about designing software solutions that enable novel user interfaces and user interactions? Do you have a passion for working on real‑time video on embedded systems? We are looking for someone who thrives on collaboration and wants to push the boundaries of what is possible in surgical robotics today! Join our team of driven and dedicated software and computer vision engineers to develop real‑time sensing and perception technologies that support novel human‑machine interfaces for next‑generation robot‑assisted surgery platforms.

We balance research and product to deliver state‑of‑the‑art experiences, innovating through the full stack, and collaborating across hardware and software teams to influence computer vision‑based deep learning algorithms roadmap that brings our vision to life.

The successful candidate must be able to apply domain expertise in a focused, small‑team environment, and must have a solid knowledge of state‑of‑the‑art deep learning techniques used for vision applications. A strong sense of shared responsibility and shared reward is required.

Intern will report to Senior Manager, Computer Vision & Machine Learning Algorithm Software, and main responsibility will be to implement state‑of‑the‑art deep learning algorithms.

• Participate, lead, and collaborate in the design and development of solution for state‑of‑the‑art deep learning algorithms.
• Play a central role in prototyping innovative algorithms in the computer vision space.
• Study and improve algorithm performance metrics that correlate with user experience, and that can be used to drive continuous improvement.
• Perform feasibility analysis and validation; develop corresponding demos.

• Study and improve algorithm performance metrics that correlate with user experience, and that can be used to drive continuous improvement.
• Study and transform data science prototypes.
• Design machine learning systems.
• Research and implement appropriate ML algorithms and tools.
• Develop machine learning applications according to requirements.
• Select appropriate datasets and data representation methods.
• Run machine learning tests and experiments.
• Perform statistical analysis and fine‑tuning using test results.
• Train and retrain systems when necessary.
• Extend existing ML libraries and frameworks.
• Keep abreast of developments in the field.
• Focus on details that are meaningful to our customer.
• Continuously explore optimal data coverage for various use cases.

• University Enrollment:
  Must be currently enrolled in and returning to an accredited degree‑seeking academic program after the internship.
• Internship Work Period:
  Must be available to work full‑time (approximately 40 hours per week) during a 10‑12 week period starting May or June. Specific start dates are shared during the recruiting process.

• Current enrollment in a Computer Science, Computer Engineering, Electrical & Computer Engineering, or related degree‑seeking program at the Master’s or Doctorate level.
• Bachelor’s level students would also be considered…