Computer Vision Software - Summer 2027 Internships

Rivian
Palo Alto, CA, United States
about 1 month ago
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Role details

Contract type
Internship / Graduate position
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Job source

Tech stack

Artificial Neural Networks Computer Vision C++ (Programming Language) Computer Engineering Python (Programming Language) Machine Learning Motion Planning Deep Learning Information Technology

Job description

Rivian internships are experiences optimized for student candidates. To be eligible, you must be an undergraduate or graduate student in an accredited program during the internship term with an expected graduation date between Fall 2027 through Spring 2029. Rivian’s Internship Program requires active student enrollment. Information regarding your expected degree completion date is collected solely to verify eligibility and determine your availability for future full-time opportunities. Rivian is an equal opportunity employer and does not use graduation dates to determine the age of applicants or as a basis for discriminatory hiring decisions. If you are not pursuing a degree, please see our full-time positions on our Rivian careers site. Note that if your university has specific requirements for internship programs, it is your responsibility to fulfill those requirements.

  • Applying to this opening will place you into consideration for Rivian’s 2026 summer internship program.
  • Teams your application can be considered for include:
  • Autonomy
  • Perception
  • Motion Planning
  • Electrical Hardware, Sensors
  • or similar

Requirements

  • Must be currently pursuing a bachelors, masters, or PhD degree at an accredited university.
  • Actively pursuing a degree or one closely related in computer science, computer engineering, electrical engineering or similar.

  • Development experience in one or more areas of computer vision, image/video, deep learning.
  • Experience programming in C++, Python, or related languages.
  • Solid understanding of machine learning, deep learning, and neural network architectures.
  • Proficiency in using computer vision and deep learning toolkits.
  • Passionately motivated to take ideas from R&D phase to a product
  • Strong written communication and presentation skills.

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