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Perception Software Engineering Intern [Fall 2024]

Logo of Zipline



4d ago

🚀 Off-cycle Internship

San Francisco

⌛ Closed
Applications are closed

Off-cycle Internship

Software Engineering•San Francisco


  • You will work in a fast-paced, collaborative environment to improve our perception capabilities. Your contributions will directly advance our production system development. Starting on day one, you will have the opportunity to work side-by-side with our perception experts to learn about and contribute to our complex perception stack. This role will focus on machine learning and deep learning projects.


  • Solid foundation in machine learning and deep learning for computer vision projects, including understanding of the theory and practice of modern machine learning techniques
  • Experience training deep-learning models for object detection in an end-to-end fashion, writing custom layers/operations, etc.
  • Experience working with Pytorch
  • Strong software engineering skills, with proficiency in relevant languages like Python, C++, or Rust
  • Experience developing solutions using test-driven methods
  • Excitement for contributing to production software
  • Excellent communication skills and ability to work across diverse teams with varying focuses

Education requirements

Currently Studying

Area of Responsibilities

Software Engineering


  • Investigate and develop computer vision algorithms and ML models for the perception system
  • Design integrated computer vision solutions that are robust to varied weather and lighting conditions while running in real-time on constrained compute
  • Build machine learning models using deep learning for computer vision tasks such as object detection and classification
  • Build software infrastructure to enable learning algorithms to leverage our large-scale fleet data
  • Understand the inner workings of neural networks to uncover edge cases and make safety determinations
  • Identify and mitigate bottlenecks in our machine learning development processes


Work type

Full time

Work mode



San Francisco