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Tech Lead Manager- MLRE, ML Systems

Scale AI· Research
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Hybrid (San Francisco, CA; New York, NY)$290.4k - $363kfull-timePosted 11mo ago

About the role

Scale's LLM post-training platform team builds an internal distributed framework for large language model training to support MLEs, researchers, data scientists, and operators for fast and automatic training and evaluation of LLMs, serving as the underlying training framework for the data quality evaluation pipeline.

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.

Qualifications

  • 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.

Skills

Required:system optimizationmulti-node LLM training and inferencedistributed ML systemsCUDAPyTorchtransformers
Nice to have:post-training methods (RLHF/RLVR)

Benefits

  • comprehensive health, dental and vision coverage
  • retirement benefits
  • a learning and development stipend
  • generous PTO
  • commuter stipend (eligible roles)
Last updated Jul 8, 2026. Interested? Apply on the company site.
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About Scale AI

Data-centric infrastructure to accelerate the development of AI

Scale accelerates the development of AI within organizations of any size to deliver critical business insights and operational efficiency. Its data-centric infrastructure platform leverages RLHF (Reinforced Learning with Human Feedback) to help organizations build the strongest AI models that supercharge their business, with customers across industries including Meta, Microsoft, U.S. Army, DoD’s Defense Innovation Unit, Open AI, General Motors, Toyota Research Institute, Brex, Instacart and Flexport.

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