- 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.
Experience & Skills Required
- Enrolled in a MS/PhD program in Computer Science, Software Engineering or similar field
- Solid understanding of GPU/CUDA
- Strong programming skills
Preferred Skills and Experience
- 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
- Shape the landscape of autonomous driving
- Work on significantly important and mission critical projects
- Extensive individual support through TuSimple’s Mentorship Program
- Competitive salary
- High full-time employment return rates after completion of Internship Program
- Gym membership reimbursement
- Monthly team building budget
- Onsite Perks (These perks will only be applicable if the internship is onsite)
- Breakfast, lunch, and dinner served every day
- Full kitchens on every floor with unlimited snacks, drinks, special treats, fruits, meals, and more