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Tesla - Palo Alto, CA

posted about 1 month ago

Full-time - Intern
Palo Alto, CA
Motor Vehicle and Parts Dealers

About the position

This position is expected to start around May/June and continue through Aug/Sep. We ask for a minimum of 12 weeks, full-time and on-site, for most internships. In this role, you will be responsible for the internal working of the AI inference stack and compiler running neural networks in millions of Tesla vehicles and Optimus. You will collaborate closely with the AI Engineers and Hardware Engineers to understand the full inference stack and design the compiler to extract the maximum performance out of our hardware. The inference stack development is purpose-driven: deployment and analysis of production models inform the team's direction, and the team's work immediately impacts performance and the ability to deploy more and more complex models. With a cutting-edge co-designed MLIR compiler and runtime architecture, and full control of the hardware, the compiler has access to traditionally unavailable features, that can be leveraged via novel compilation approaches to generate higher performance models.

Responsibilities

  • 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

Requirements

  • Pursuing a degree in Computer Science, Computer Engineering, or relevant field of study with a graduation date between 2025 -2026
  • Must be able to relocate and work on site in Palo Alto, CA
  • Strong C++ programming skills and familiarity with Python
  • Solid understanding of machine learning concepts and fundamentals
  • Capable of delivering results with minimal oversight

Nice-to-haves

  • Experience with quantization, MLIR, CUDA, and LLMs is a huge plus
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