AI Infrastructure Intern — LLM Optimization & Deployment

TikTok

Singapore

On-site

SGD 20,000 - 27,000

Full time

16 hours ago
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Job summary

TikTok is seeking interns to join the E-commerce Recommendation Infra team in Singapore. You will research and implement LLM-based recommendation foundations, and build optimization toolchains for large-scale deployment in a fast-growing e-commerce context.

Candidates should be pursuing a CS/CE/IS degree and have hands-on experience with C++/CUDA/Python and DL frameworks like PyTorch or TensorFlow. Prior exposure to Megatron-LM or DeepSpeed is a plus.

Qualifications

  • Currently pursuing a Bachelor's or Master's degree in Computer Science, Computer Engineering, Information Systems, or a related technical discipline
  • Solid programming skills in C++/CUDA/Python, with basic understanding of GPU architecture and distributed training
  • Familiarity with deep learning frameworks (PyTorch, TensorFlow) and basic knowledge of LLMs

Responsibilities

  • Research and implement LLM-based recommendation foundation model training and inference optimization technologies for e-commerce scenarios
  • Build model optimization toolchains including quantization, pruning, and distillation for deep learning frameworks
  • Design and implement distributed inference serving architectures supporting large-scale LLM deployment for recommendation use cases

Skills

C++/CUDA/Python
GPU architecture
Distributed training
Deep learning frameworks
LLM inference acceleration

Education

Bachelor’s or Master’s in CS/CE/IS

Tools

PyTorch
TensorFlow
Megatron-LM
DeepSpeed
TensorRT-LLM

Job description

TikTok is seeking interns to join the E-commerce Recommendation Infra team in Singapore. You will research and implement LLM-based recommendation foundations, and build optimization toolchains for large-scale deployment in a fast-growing e-commerce context.

Candidates should be pursuing a CS/CE/IS degree and have hands-on experience with C++/CUDA/Python and DL frameworks like PyTorch or TensorFlow. Prior exposure to Megatron-LM or DeepSpeed is a plus.

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