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Internship, Software Engineer, Autopilot Inference (Summer 2024)

What to Expect

Consider before submitting an application:

This position is expected to start around May 2024 and continue through the entire Summer 2024 term or into Winter 2024 if available. We ask for a minimum of 12 weeks, full-time and on-site, for most internships.

International Students: If your work authorization is through CPT, please consult your school on your ability to work 40 hours per week before applying. You must be able to work 40 hours per week on-site. Many students will be limited to part-time during the academic year.


As a member of the Autopilot group, you will have the opportunity to apply your technical skills to a variety of system components & foundational code targeting higher performance of Autopilot and our Humanoid robot. You will participate in the development of the internal working of the AI inference (export/compiler/runtime/deployment) stack running Neural Networks in millions of Tesla cars. Having experience or familiarity with Computer Vision, Machine Learning & related software concepts is a plus.

What You’ll Do

  • Take ownership of parts of AI Inference stack (Export/Compiler/Runtime) (flexible, based on skills/interests/needs)
  • Closely collaborate with AI team to guide them on the design and the development of Neural Networks into production
  • Collaborate with HW team to understand current HW architecture and propose future improvements
  • Develop algorithms to improve performance and reduce compiler overhead
  • Debug functional and performance issues on massively-parallel systems
  • Work on architecture-specific neural network optimization algorithms for high performance computing

What You’ll Bring

  • Currently pursuing a degree in Computer Science & Engineering, or a related field
  • Comfortable with C++ and Python
  • Capable of delivering results with minimal oversight
  • Bonus: Senior level candidates with prior industry experience. Please include anticipated graduation date on resume