Large Language Model Pre-training Engineer

Job Responsibilities

• Pre-training Strategy & Architecture
• Pre-training Data Engineering
• Large-scale Distributed Training
• Long-context Training
• Training Monitoring & Optimization
• Evaluation & Iterative Optimization

Job Requirements

Bachelor's degree or above in Computer Science, Artificial Intelligence, NLP, Machine Learning, Distributed Systems, or a related field.

LLM Pre-training Experience

• Hands-on experience with complete LLM pre-training projects.
• Experience participating in the pre-training of 7B+ parameter models.

Distributed Training

• Strong expertise in large-scale distributed training frameworks such as Megatron-LM, DeepSpeed, or FSDP.
• Practical experience with 64+ GPU training environments.

Pre-training Data Engineering

• Solid understanding of large-scale pre-training data pipelines, including data cleaning, deduplication, quality filtering, tokenization, data mixing, and data quality optimization.

Training Monitoring & Debugging

• Strong ability to analyze training loss, gradients, convergence, and training stability.
• Experience troubleshooting large-scale distributed training issues.

Long-context Training

• Familiarity with long-context training and extension techniques, including RoPE scaling, NTK-aware interpolation, and YaRN.

Preferred Qualifications

• Experience with 70B+ parameter model pre-training.
• Experience with MoE (Mixture-of-Experts) model pre-training.
• Publications in top-tier AI/ML conferences such as NeurIPS, ICML, ICLR, ACL, or EMNLP, particularly in LLM pre-training, model architecture, or training optimization.
• Experience optimizing large-scale GPU clusters and training infrastructure.