ByteDance
GPU/AI Application System Software Engineer Intern (System Technologies and Engineering) - 2027 Summer
San Jose, California · Internship · Posted Oct 28, 2026
- Education
- Currently pursuing a Bachelor's or Master's degree in Electrical Engineering, Computer Engineering, Computer Science, or a related major.
About the job
Develop system benchmarks and automation tools, then diagnose and optimize performance for large-scale AI and HPC workloads across operating systems and hardware.
What you'll do
- Design and implement system performance benchmarks and testing methodologies.
- Develop tools and optimize AI workloads for large-scale LLM training, inference, and HPC; automate benchmark testing with Python scripts.
- Collaborate with internal teams to identify system bottlenecks, debug issues, and improve performance.
What they ask for
- Currently pursuing a Bachelor's or Master's degree in Electrical Engineering, Computer Engineering, Computer Science, or a related major.
- Deep understanding of operating systems, Linux Kernel, and computer architecture.
- Background in GPU/CPU benchmarking and hands-on experience with Linux-based systems.
- Familiarity with ML/DL techniques, algorithms, and frameworks such as TensorFlow or PyTorch; exposure to testing automation.
Nice to have
- Background in HPC, ML hardware acceleration (e.g., GPU/TPU/RDMA), ML for Systems, or distributed storage; AI model development, training, evaluation, or deployment experience.
- Parallel programming and a communication runtime (MPI, NCCL, UCX, NVSHMEM); Linux kernel development or complex system-level debugging experience.
Tools
Python, TensorFlow, PyTorch, Linux Kernel, MPI, NCCL, UCX, NVSHMEM
AI focus
Benchmark and optimize large-scale LLM training and inference workloads, and support AI/HPC system performance across the hardware/software stack.
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