The opportunity
Scale's LLM post-training platform team builds our internal distributed framework for large language model training. The platform powers MLEs, researchers, data scientists, and operators for fast and automatic training and evaluation of LLMs.
What you'll do
Build, profile and optimize our training and inference framework.
Collaborate with ML and research teams to accelerate their research and: development, and enable them to develop the next generation of models and data curation.
Research and integrate state-of-the-art technologies to optimize our ML system.
Passionate about system optimization
Experience with multi-node LLM training and inference
Experience with developing large-scale distributed ML systems
What they're looking for
- Experience with post-training methods like RLHF/RLVR and related algorithms like PPO/GRPO etc.
- Strong software engineering skills, proficient in frameworks and tools such: as CUDA, Pytorch, transformers, flash attention, etc.
- Strong written and verbal communication skills to operate in a cross functional team environment.
- Demonstrated expertise in post-training methods and/or next generation use: cases for large language models including instruction tuning, RLHF, tool use, reasoning, agents, and multimodal, etc.
