ML Research Engineer, ML Systems
About the role
Scale’s ML platform (RLXF) team builds an internal distributed framework for large language model training and inference to power researchers, data scientists, and operators. The role focuses on building and optimizing the foundation platform to support ML research, development, training, inference, and data curation across Scale’s ML teams.
Responsibilities
- Build, profile and optimize our training and inference framework
- Collaborate with ML 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
- Strong excitement about system optimization
- Experience with multi-node LLM training and inference
- Experience with developing large-scale distributed ML systems
- Strong software engineering skills, proficient in frameworks and tools such as CUDA, Pytorch, transformers, flash attention, etc.
- Strong written and verbal communication skills and the ability to operate in a cross functional team environment
Skills
Benefits
- comprehensive health, dental and vision coverage
- retirement benefits
- learning and development stipend
- generous PTO
- commuter stipend (potential)
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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