Computer Vision R&D Internship

Company Description

At Intuitive, we are united behind our mission: we believe that minimally invasive care is life-enhancing care. Through ingenuity and intelligent technology, we expand the potential of physicians to heal without constraints.

As a pioneer and leading company in the field of robotic-assisted surgery, we strive to foster an inclusive and diverse team, committed to making a difference. For more than 25 years, we have worked with hospitals and care teams around the world to help solve some of healthcare’s hardest challenges and advance what is possible.

Intuitive has been built by the efforts of great people from diverse backgrounds. We believe great ideas can come from anywhere—we strive to foster an inclusive culture built around diversity of thought and mutual respect. We lead with inclusion and empower our team members to do their best work as their most authentic selves.

Passionate people who want to make a difference drive our culture—our team members are grounded in integrity, have a strong capacity to learn, the energy to get things done, and bring diverse, real-world experiences to help us think in new ways. We actively invest in our team members to support their long-term growth so they can continue to advance our mission and achieve their highest potential. 

Join a team committed to taking big leaps forward for a global community of healthcare professionals and their patients. Together, let’s advance the world of minimally invasive care.

Job Description

Contract Duration: 3 to 4 months 
Location: Aubonne - fully onsite 

Primary Function of Position:

We are seeking a Machine Learning Engineer to join the Intraoperative Intelligence Group at Intuitive Surgical. In this role, you will contribute to the exploration and development of innovative product concepts aimed at advancing imaging-based intelligent robotic surgery.

Roles and Responsibilities:

Under the guidance of a mentor, you will:

• Develop and implement machine learning algorithms for surgical scene perception.
• Evaluate algorithm performance in ex-vivo and in-vivo laboratory environments.
• Collect, curate, and analyze data to iteratively improve model performance based on experimental feedback.
• Collaborate with cross-functional teams to translate research concepts into practical solutions.

Qualifications

Required Knowledge, Skills, and Experience:

• Currently enrolled in a PhD program in Computer Science, Engineering, or a related field in a University.
• Strong proficiency in PyTorch.
• Solid experience developing applications in Python.
• Experience with C++ is a plus.
• Experience with CUDA is a plus.
• Familiarity with generative image models is a plus.
• Self-motivated, with the ability to work effectively in a collaborative, results-oriented environment.