GPU/AI Platform Engineer Intern — Systems Performance

ByteDance; San Jose (CA); Hybrid; USD 34,000 - 48,000; Part time

Job summary

ByteDance in San Jose seeks an intern to contribute to GPU/AI platform research and optimization. You will develop benchmarks, tools, and performance techniques to drive/system performance for next‑gen systems while collaborating with a skilled Technology team.

The role targets PhD candidates in EE/CS, with deep system knowledge and strong C/C++ and Python skills, offering hands-on experience in architecture and industry tech within a global company.

Qualifications

• PhD candidate in Electrical Engineering, Computer Engineering, Computer Science, or related field.
• Thesis on GPU/AI platform architecture or software-hardware co-design.
• Deep understanding of GPU/AI SoC architecture, interconnect, memory subsystems.
• Experience in GPU/AI system performance optimization or software-hardware co-design.
• Strong C/C++ and Python programming skills.

Responsibilities

• Develop application benchmarks, tools and performance optimization method for GPU/AI system.
• Identify bottlenecks with data-driven study; lead SW-HW co-design efforts.
• Develop GPU/AI system TCO model from benchmarks and performance data.
• Collaborate with industry consortia to explore emerging standards and technologies.
• Coordinate with partners to set up POC or prototypes for testing.

Skills

C/C++

Python

GPU/AI architecture

Performance optimization

Software-hardware co-design

Education

PhD in EE/CE/CS

Job description

ByteDance in San Jose seeks an intern to contribute to GPU/AI platform research and optimization. You will develop benchmarks, tools, and performance techniques to drive/system performance for next‑gen systems while collaborating with a skilled Technology team.

The role targets PhD candidates in EE/CS, with deep system knowledge and strong C/C++ and Python skills, offering hands-on experience in architecture and industry tech within a global company.