LLM Engineer (LLM Training)

The role

LLM Engineer (LLM Training) designs LLM training pipelines to train generative language models for real services. The role involves improving training efficiency and designing learning structures for self-refinement to improve quality.

What you will do

• Improve efficiency of the LLM training process
• Improve overall efficiency of Pre-training and Post-training processes
• Improve overall accuracy and stability of generation results
• Design learning structures capable of Self-Refine to improve generation quality

Required qualifications

• 3+ years of experience in Deep Learning or NLP (Master's graduates may apply)
• Broad research and development experience related to Deep Learning or NLP
• Proficient programming skills (Python & pytorch)
• Experience in model design, training, evaluation, and optimization using PyTorch
• Ability to perform LLM training and troubleshooting using GPU
• Experience using distributed training frameworks (Slurm, DDP, Horovod, etc.)

Nice to have

• Deep Learning/NLP related paper submission or holding a Master's or Doctoral degree
• Experience presenting papers at major academic conferences (ACL, EMNLP, NeurIPS, etc.)
• Experience with Docker and Kubernetes
• Experience designing and managing training pipelines using GPU clusters
• Experience in training and service development using GPU
• Experience in building GPU-based Training or Inference systems
• Experience related to LLM Post-training
• Experience using Supervised Fine-Tuning and Parameter Efficient Fine-Tuning

Before you apply

• Document screening
• Coding test
• 1st interview (Video, approx. 1 hour)
• 2nd interview (In-person or Video, approx. 3 hours)
• Reference check may be conducted after the interview process with candidate consent

About the company

42dot designs LLM training pipelines to train generative language models for real services.