ByteDance
Tech Lead, Research Scientist - DPU & AI Infra
San Jose, California · Full-time · Posted Oct 28, 2026
- Experience
- 5+ years of relevant industry experience; exception for Ph.D. with strong background.
- Education
- B.S./M.S. in Computer Science, Computer Engineering, or related fields; or Ph.D. with strong research/publications.
About the job
Designs high-performance DPU networking software and co-designed hardware/software systems, while advancing infrastructure acceleration for distributed AI training and inference.
What you'll do
- Develop reliable, low-latency DPU network software and optimize performance from OS kernels and drivers to user-space runtimes.
- Collaborate with hardware teams on networking and storage acceleration, and explore DPU/GPU acceleration for distributed training and inference.
- Contribute to architecture, technical proposals, and long-term research directions.
What they ask for
- B.S./M.S. in Computer Science, Computer Engineering, or a related field, or a Ph.D. with strong research/publications.
- Proficiency in C/C++ development and debugging, plus strong Linux systems development experience.
- Solid understanding of compute, network architecture, and operating systems.
- Background in at least one of software-hardware co-design, distributed systems, high-performance networking, or AI/ML systems.
Nice to have
- Ph.D. in a related field with research training and publications.
- Experience with hardware acceleration, network virtualization, DPDK, NCCL Collectives, or AI/ML infrastructure systems.
Tools
C/C++, Linux, DPDK, RDMA, OVS, SR-IOV, eBPF, CUDA
AI focus
Explore infrastructure acceleration for distributed AI/ML training and inference using DPUs, GPUs, and custom hardware; preferred experience includes inference KV cache systems, data preprocessing, NCCL Collectives, AI communication patterns, and parallelization techniques.
Model-written summary · the original posting is authoritative