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Scale AIScale AISan Francisco, CA

Machine Learning Systems Research Engineer, Agent Post-training - Enterprise GenAI

Develops and optimizes post-training algorithms for agent RL platforms, focusing on LLM training, inference frameworks, and multi-agent systems. Requires 1-3 years production LLM experience, expertise in PyTorch/CUDA, RLHF/PPO, and advanced degree.

218k – 273k/yr
On-site1+ YOEAI Research

About the role

Responsibilities

  • Build, profile and optimize our training and inference framework.
  • Post-train state of the art models, developed both internally and from the community, to define stable post-training recipes for our enterprise engagements.
  • Collaborate with ML teams to accelerate their research and development, and enable them to develop the next generation of models and data curation.
  • Create a next-gen agent training algorithm for multi-agent/multi-tool rollouts.

Requirements

  • At least 1-3 years of LLM training in a production environment
  • Passionate about system optimization
  • Experience with post-training methods like RLHF/RLVR and related algorithms like PPO/GRPO etc.
  • Ability to demonstrate know-how on how to operate the architecture of the modern GPU cluster
  • Experience with multi-node LLM training and inference
  • 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.
  • PhD or Masters in Computer Science or a related field

Skills

PyTorchCUDATransformersFlash AttentionRLHFRlvrPpoGrpoGpu ClusterMulti-Node Training

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