Recommendation Architecture AI/ML Infrastructure Engineer Graduate (Data-Arch-TikTok Live) - 2027 Start

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 system bottlenecks and improve performance, including through GPU optimization and efficient communication.

What they ask for

• Completing or recently completed a Bachelor's or Master's degree in Artificial Intelligence, Software Development, Computer Science, Computer Engineering, or a related discipline.
• Strong programming skills in C++ or Python, with 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 through research, internships, or open-source projects; familiarity with distributed training concepts.
• GPU programming with CUDA, Triton, or similar technologies; knowledge of LLM serving techniques or relevant open-source or research contributions.

Tools

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

AI focus

Develop infrastructure for recommendation models and LLMs, including large-scale model training, online inference, GPU optimization, and LLM training and serving.