Tech Lead Manager- MLRE, ML Systems

Overview

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. It also serves as the underlying training framework for the data quality evaluation pipeline. Scale is uniquely positioned at the heart of the field of AI as an indispensable provider of training and evaluation data and end-to-end solutions for the ML lifecycle.

You will work closely with Scale's ML teams and researchers to build the foundation platform which supports all our ML research and development works. You will be building and optimizing the platform to enable our next generation LLM training, inference and data curation.

• 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.

• 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.

• 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 capabilities.

Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The base salary range for this full-time position in San Francisco, New York, and Seattle is $264,800 – $331,000 USD. Benefits include comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. The role may be eligible for additional benefits such as a commuter stipend.

Salary ranges are determined by location and other factors; your recruiter can share specifics for your location during the hiring process.

We are an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We provide reasonable accommodations in the application or recruiting process upon request. If you need assistance, please contact  We comply with the U.S. Pay Transparency and related laws.

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