ML Engineering 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 bigger than yourself and help transform the future of healthcare, you’ll find your purpose here.

Job Description

Primary Function of Position

We are looking for a talented individual to join our growing machine learning and data science team to help provide creative ways to develop new technology focused on surgical workflow and performance for next generation robotic surgery platforms.

As a Machine Learning Engineer Intern, you will work at the intersection of machine learning and engineering (i.e., MLOps) to contribute to innovative digital solutions leveraging Surgical AI/ML technologies. You will be reporting to the Manager of MLOps Engineering within the Digital Organization at Intuitive.

Essential Job Duties

• Working closely with Machine Learning and Data/Software Engineering teams to develop efficient processes for model development/deployment for various applications.

• Developing automated workflows and tools to curate datasets and facilitate training of deep learning models

• Integrating machine learning into digital products and services by working cross-functionally across engineering, data science, and machine learning teams

Qualifications

Required Skills and Experience

University Hiring Program Eligibility Requirements:

• 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.

Required Education and Training

• Current enrollment in an Computer Science, Computer Engineering, Electrical & Computer Engineering, or related degree-seeking program at the Master’s, or Doctorate level.

• Excellent communication skills both written and verbal

• A desire to work in a high-energy, focused, small-team environment with a sense of shared responsibility and shared reward

• Interest in early research and development through to product roll-out in the fields of surgical AI and surgical robotics

• Hands-on experience with ML frameworks, such as PyTorch, Tensorflow, or similar

• Knowledgeable about MLOps platforms and/or ML CI/CD workflows to manage datasets and model training, deployment, and monitoring

• Experience with MLOps tools like MLFlow, KubeFlow, W&B, etc

• Knowledgeable on cloud compute environments such as AWS, GCP, etc

• Experience with Python and SQL

• Experience with Git e.g github, gitlab, bitbucket, etc

Preferred Skills and Experience

• Knowledgeable in launching ML models into production

• Experience supporting large multi-modality dataset including image/video

• Experience in developing ML applications within healthcare

Additional Information

Due to the nature of our business and the role, please note that Intuitive and/or your customer(s) may require that you show current proof of vaccination against certain diseases including COVID-19.  Details can vary by role.

Intuitive is an Equal Opportunity Employer. We provide equal employment opportunities to all qualified applicants and employees, and prohibit discrimination and harassment of any type, without regard to race, sex, pregnancy, sexual orientation, gender identity, national origin, color, age, religion, protected veteran or disability status, genetic information or any other status protected under federal, state, or local applicable laws.