AI Foundation Model Infrastructure Intern - Seed

ByteDance; Seattle (WA); On-site; USD 35,817 - 59,236; Full time

Benefits offered by this job

Health insurance

Housing allowance

10 paid holidays per year

Paid sick time

Job summary

ByteDance seeks a Seed Infrastructure Intern in Seattle to contribute to large-scale AI infrastructure, including training platforms and inference systems. You will work with researchers and engineers to optimize system modules and tooling across distributed components.

Qualifications include pursuing a CS/Math/Engineering degree and strong Python or C/C++ skills, with experience in systems programming or distributed computing from coursework or projects.

Qualifications

• Pursuing a Bachelor's or Master's degree in computer science, mathematics, engineering, or a related field.
• Strong programming skills and solid foundation in algorithms, data structures, and systems, proficient in Python or C/C++.
• Experience with systems programming, distributed systems, compilers, or performance optimization through coursework, research, or projects.

Responsibilities

• Contribute to infrastructure and systems for large-scale models.
• Support development of efficient and scalable components across training platforms, inference systems, compilers, and distributed systems.
• Implement and optimize system modules, tooling, or frameworks.
• Collaborate with researchers and engineers to support research and system development.

Skills

Python

C/C++

Algorithms & DS

Distributed systems

Education

Bachelors/Masters in CS/Math/Engineering

Tools

GCC/Clang

Linux

Job description

ByteDance seeks a Seed Infrastructure Intern in Seattle to contribute to large-scale AI infrastructure, including training platforms and inference systems. You will work with researchers and engineers to optimize system modules and tooling across distributed components.

Qualifications include pursuing a CS/Math/Engineering degree and strong Python or C/C++ skills, with experience in systems programming or distributed computing from coursework or projects.