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Software Engineer Intern, ML Accelerator/GPU Programming


Software Engineer Intern, ML Accelerator/GPU Programming

Cambridge, MA
+11 locations
New York, NY
Ithaca, NY
Pittsburgh, PA
Ann Arbor, MI
Chicago, IL
Urbana, IL
Austin, TX
San Diego, CA
San Francisco, CA
Stanford, CA
Berkeley, CA
  • Responsibilities

    Job Description

    This role is located in San Diego.For immediate consideration, please send you resume to:

    COMPANY OVERVIEW Come join a higher calling and find a deeper purpose! TuSimple is disrupting the world by developing an entirely new method of freight delivery. Our AFN (Autonomous Freight Network) will change every aspect of commercial ground freight transportation (truck, train, pipeline) As a global Artificial Intelligence Technology Company, we are the epicenter of the Autonomous Vehicle Universe. Our breakthroughs are multiple generations ahead of anyone in the world. While inventing the framework of Autonomous Driving, our current fleet of autonomous Trucks are helping communities receive much-needed supplies and medical equipment around the clock. Our people are some of the most talented engineers and contributors who are leaving behind a historic legacy.
    TuSimple was founded half a decade ago with the goal of bringing the TOP MINDS in the world together to achieve the dream of a driver less truck solution. With a foundation in computer vision, algorithms, mapping, and Artificial Intelligence, TuSimple is working to create the first global commercially viable autonomous freight network. At Tusimple, the Heterogeneous Computing team is responsible for optimizing algorithm performance through hardware accelerators, improving accelerator utilization, as well as maintaining the stability of the whole system.

    Example projects we are working on include:

    • Accelerating existing algorithms using CUDA and GPU.
    • Minimizing hardware resource usage, e.g. GPU memory footprint, through proper resource management.
    • Building GPU-accelerated Machine Learning Library.


    • Test, bench, and build tools for benchmarking ML algorithms on the hardware accelerator.
    • Design and develop new GPU operators with high-quality codes.
    • Analyze the software and identify potential performance bottlenecks.


    • BS/MS in Computer Science or other related fields
    • Solid understanding of GPU/CUDA
    • Strong programming skills


    • Development experiences in Machine Learning Libraries, such as PyTorch, TensorFlow, TVM, MXNet
    • Experience in arm-based embedded systems/Nvidia Drive products
    • Strong System Skills (Operating System, Parallel Computing, Computer Architecture)


    • Work with world class AI Engineers
    • Competitive monthly compensation
    • Shape the landscape of autonomous driving
    • Daily breakfast, lunch, and dinner
    • Full kitchen with unlimited snacks and fruits

    For immediate consideration, please send you resume to:

  • Locations
    San Diego, CA • San Francisco, CA • Stanford, CA • Berkeley, CA • Chicago, IL • Urbana, IL • Cambridge, MA • Ann Arbor, MI • New York, NY • Ithaca, NY • Pittsburgh, PA • Austin, TX