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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