Recommendation Architecture AI/ML Infrastructure Engineer Intern (Data-Arch-TikTok Live) - 2027 Summer

What you'll do

• Build and optimize infrastructure for large-scale model training and online inference.
• Develop distributed systems for recommendation models and LLMs, and collaborate with researchers on LLM training and serving.
• Analyze bottlenecks and improve performance through GPU optimization and efficient communication.

What they ask for

• Currently pursuing a Bachelor’s or Master’s degree in Artificial Intelligence, Software Development, Computer Science, Computer Engineering, or a related technical discipline.
• Strong programming skills in C++ or Python and a good understanding of data structures, algorithms, and computer systems.
• Familiarity with PyTorch or TensorFlow.
• Knowledge of Transformer architectures and Large Language Models (LLMs).

Nice to have

• Hands-on LLM training or inference experience; familiarity with distributed training concepts such as DP, TP, PP, FSDP, or ZeRO.
• Experience with CUDA, Triton, or similar GPU programming technologies; understanding of LLM serving techniques such as KV Cache, Continuous Batching, or FlashAttention.

Tools

C++, Python, PyTorch, TensorFlow, CUDA, Triton, FSDP, ZeRO

AI focus

Develops infrastructure for large-scale recommendation models and LLM training and inference, including distributed systems, GPU optimization, and serving.