ByteDance

1 day ago

Student Researcher (AI Foundation Models Infrastructure - Seed Infra) - 2026 Start (PhD)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 23 hours agoStatus: Live

Job Summary

Join the Seed Infrastructures team to help build and optimize AI foundation model infrastructure. You’ll work on large-scale distributed training systems, reinforcement learning training and post-training pipelines, and high-performance inference to improve latency and throughput. You may also develop compiler/runtime optimizations for heterogeneous GPU/accelerator hardware, perform system-level profiling and bottleneck diagnosis, and build tooling and automation to improve reliability and developer productivity.

Location: San Jose

Workplace: Onsite

Employment Type: Internship

Job Function: Research & Scientific (R&D)

Seniority: Intern level

Key Responsibilities

•Design and optimize large-scale distributed training systems, including parallelism, memory efficiency, and fault tolerance.
•Contribute to reinforcement learning training frameworks and large-scale post-training systems.
•Improve inference performance by optimizing latency and throughput for foundation models.
•Develop compiler or runtime optimizations for heterogeneous hardware (GPU/accelerators).
•Perform system-level performance analysis, profiling, bottleneck diagnosis, and build tooling/automation to improve reliability and developer productivity.

Key Requirements

•Currently pursuing a PhD in Computer Science, Electrical Engineering, or related technical fields.
•Strong programming skills in Python and/or C++.
•Solid understanding of systems, distributed computing, machine learning systems, or performance optimization.
•Experience with one or more areas such as distributed training frameworks (e.g., PyTorch FSDP, Megatron-style parallelism), reinforcement learning training systems, GPU programming (CUDA, Triton), compiler technologies, large-scale inference optimization, or performance profiling and systems debugging.
•Strong problem-solving skills and ability to work in fast-paced, research-driven environments.

Education:PhD / Doctorate in Computer Science, Electrical Engineering, or related technical fields

Skills:Problem-solvingAbility to work in fast-paced environments

Tech Stack:PythonC++PyTorch FSDPMegatron-style parallelismCUDATritonGPU programmingDistributed training frameworksReinforcement learningInference optimizationPerformance profiling

Company Brief

ByteDance

Develops consumer internet and content platforms, including TikTok and other apps for short-form video, news, and entertainment. It also builds advertising, commerce, and creator tools that connect audiences, brands, and publishers across global markets.

Industry: Digital Media

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Established Company

Headquarters: Beijing, China

Founded: 2012

Website LinkedIn

Loading job details...

Preparing the role view and application actions.

ByteDance

1 day ago

Student Researcher (AI Foundation Models Infrastructure - Seed Infra) - 2026 Start (PhD)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 23 hours agoStatus: Live

Job Summary

Location: San Jose

Workplace: Onsite

Employment Type: Internship

Job Function: Research & Scientific (R&D)

Seniority: Intern level

Key Responsibilities

•Design and optimize large-scale distributed training systems, including parallelism, memory efficiency, and fault tolerance.
•Contribute to reinforcement learning training frameworks and large-scale post-training systems.
•Improve inference performance by optimizing latency and throughput for foundation models.
•Develop compiler or runtime optimizations for heterogeneous hardware (GPU/accelerators).
•Perform system-level performance analysis, profiling, bottleneck diagnosis, and build tooling/automation to improve reliability and developer productivity.

Key Requirements

•Currently pursuing a PhD in Computer Science, Electrical Engineering, or related technical fields.
•Strong programming skills in Python and/or C++.
•Solid understanding of systems, distributed computing, machine learning systems, or performance optimization.
•Experience with one or more areas such as distributed training frameworks (e.g., PyTorch FSDP, Megatron-style parallelism), reinforcement learning training systems, GPU programming (CUDA, Triton), compiler technologies, large-scale inference optimization, or performance profiling and systems debugging.
•Strong problem-solving skills and ability to work in fast-paced, research-driven environments.

Education:PhD / Doctorate in Computer Science, Electrical Engineering, or related technical fields

Skills:Problem-solvingAbility to work in fast-paced environments

Tech Stack:PythonC++PyTorch FSDPMegatron-style parallelismCUDATritonGPU programmingDistributed training frameworksReinforcement learningInference optimizationPerformance profiling

Company Brief

ByteDance

Industry: Digital Media

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Established Company

Headquarters: Beijing, China

Founded: 2012

Website LinkedIn