Scale AI Tech Lead Manager at Scale AI leads development and optimization of the LLM post-training platform. Responsibilities include building training and inference frameworks and collaborating with ML teams to accelerate research.
Responsibilities
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.
Ideally you’d have:
Passionate about system optimization
Experience with multi-node LLM training and inference
Experience with developing large-scale distributed ML systems
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.
Qualification
Strong software engineering skills
Required
Experience with multi-node LLM training and inference
Experience with developing large-scale distributed ML systems
Experience with post-training methods like RLHF/RLVR and related algorithms like PPO/GRPO
Strong software engineering skills
Strong written and verbal communication skills
Preferred
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.
