Cloud DPU & AI Infrastructure Acceleration Engineer

ByteDance; Seattle (WA); Hybrid; USD 154,000 - 301,000; Full time

Job summary

ByteDance is seeking a highly capable DPU Software Engineer to design and implement high-performance network software for data processing units. You will collaborate with hardware teams on software-hardware co-design for networking and storage acceleration and explore AI/ML infrastructure acceleration to optimize distributed training and inference.

The role emphasizes end-to-end performance tuning, from kernel space to user-space runtimes, and contributing to long-term research directions within

Qualifications

• BS/MS in Computer Science, Computer Engineering, or related fields; or Ph.D. with strong research/publications.
• 2+ years of relevant industry experience (exception for Ph.D. with strong background).
• Proficiency in C/C++ development and debugging.
• Strong Linux systems development experience.
• Solid understanding of compute, network architecture, and operating systems.
• Background in software-hardware co-design, distributed systems, high-performance networking, or AI/ML systems.
• Ph.D. preferred with research training and publications.

Responsibilities

• Design and develop DPU network software with a focus on high performance, low latency, and reliability.
• Collaborate with hardware teams to build software-hardware co-design solutions for networking and storage acceleration.
• Explore AI/ML infrastructure acceleration, leveraging DPUs, GPUs, and custom hardware to optimize distributed training and inference.
• Drive end-to-end performance optimization, from OS kernels and drivers to user-space runtime systems.
• Contribute to architecture design, technical proposals, and long-term research directions.

Skills

C/C++ development

Linux development

Compute/Networking/OS

Education

BS/MS in CS/CE (or PhD)

Tools

DPDK

OVS

SR-IOV

eBPF

Job description

ByteDance is seeking a highly capable DPU Software Engineer to design and implement high-performance network software for data processing units. You will collaborate with hardware teams on software-hardware co-design for networking and storage acceleration and explore AI/ML infrastructure acceleration to optimize distributed training and inference.

The role emphasizes end-to-end performance tuning, from kernel space to user-space runtimes, and contributing to long-term research directions within