AI Infra Engineer Intern: Scale LLMs & GPUs

TikTok; San Jose (CA); On-site; USD 51,000 - 73,000; Full time

Benefits offered by this job

Housing allowance

Job summary

TikTok is seeking a passionate Software Engineer Intern to join the Model Infrastructure team, building infrastructure for large-scale model training and online inference powering our recommendation systems and LLMs.

You will work on distributed training, GPU optimization, and collaborating with researchers to deploy LLM training and serving solutions. This internship offers hands-on experience and opportunities for personal and professional growth.

Qualifications

• Currently pursuing a Bachelor's degree in Computer Science or a related discipline.
• Strong programming skills in C++ or Python.
• Good understanding of data structures, algorithms, and computer systems.
• Familiarity with PyTorch or TensorFlow.
• Knowledge of Transformer architectures and Large Language Models (LLMs).
• Strong problem-solving skills and a passion for building large-scale AI systems.

Responsibilities

• Build and optimize infrastructure for large-scale model training and online inference.
• Develop distributed systems supporting large recommendation models and LLMs.
• Improve training and inference performance through GPU optimization and efficient communication.
• Collaborate with researchers to develop and deploy LLM training and serving solutions.
• Analyze system bottlenecks and implement performance optimizations.

Skills

C++ or Python

Data structures & algorithms

PyTorch or TensorFlow

LLM knowledge

Problem solving

Education

Bachelor's in Computer Science or related (pursuing)

Master's in Computer Science or related (preferred)

Tools

CUDA

Triton

Distributed training

KV Cache / FlashAttention

Job description

TikTok is seeking a passionate Software Engineer Intern to join the Model Infrastructure team, building infrastructure for large-scale model training and online inference powering our recommendation systems and LLMs.

You will work on distributed training, GPU optimization, and collaborating with researchers to deploy LLM training and serving solutions. This internship offers hands-on experience and opportunities for personal and professional growth.