ML Research Engineer, ML Systems - Scale AI : Job Details

Scale's ML platform (RLXF) team builds our internal distributed framework for large language model training and inference. The platform powers MLEs, researchers, data scientists, and operators for fast and automatic training and evaluation of LLMs, as well as data quality assessment.

Scale is positioned at the core of AI as a provider of training data, evaluation data, and end-to-end ML lifecycle solutions. You will collaborate across Scale's ML teams and researchers to develop the foundational platform supporting all our ML research and development. Your role involves building and optimizing the platform to enable next-generation LLM training, inference, and data curation.

If you are passionate about shaping the future of AI through innovation, we want to hear from you!

• Build, profile, and optimize our training and inference framework
• Collaborate with ML teams to accelerate research and enable the development of new models and data curation methods
• Research and integrate cutting-edge technologies to enhance our ML systems

• Strong enthusiasm for system optimization
• Experience with multi-node LLM training and inference
• Experience developing large-scale distributed ML systems
• Proficiency in frameworks and tools like CUDA, PyTorch, transformers, flash attention, etc.
• Excellent communication skills and the ability to work effectively in a cross-functional team

• Expertise in post-training methods and next-generation use cases for large language models, including instruction tuning, RLHF, tool use, reasoning, agents, and multimodal applications

Compensation packages include base salary, equity, and benefits. The salary range for this position in San Francisco, New York, and Seattle is $200,800—$251,000 USD, depending on location and experience. Benefits include health coverage, retirement plans, a learning stipend, PTO, and potential additional perks.

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