Machine Learning Research Intern (Summer 2027)
About the role
Scale’s Machine Learning Research Intern role focuses on deep technical ML applications in production and cutting-edge research problems, with mentorship from researchers and collaboration with industry and academia. Interns own real, published or shipped work.
Responsibilities
- Measure the dangerous capabilities of frontier models and conduct preparedness research
- Research the science and creation of new benchmarks for frontier models
- Develop new methods for training models to excel on extremely difficult reasoning problems that require long chains of thought
- Research reinforcement learning and post-training methods that improve model reliability on high-stakes tasks
- Research scalable oversight protocols that enable humans to produce and quality control reasoning chains beyond their native capabilities
- Study the boundaries of model generalization and capabilities to inform data-driven advancements
- Research synthetic and hybrid data with humans in the loop to scale up high-quality data generation
- Take models currently in production, identify areas for improvement, improve them using retraining and hyperparameter searches, then deploy without regressing on core model characteristics
- Create post-training or agentic solutions that integrate into our ability to deliver applications for enterprise and public sector clients
Qualifications
- Currently enrolled in a BS, MS or PhD program with a focus on Machine Learning, Deep Learning, or Natural Language Processing, with a graduation date in Fall 2027 or Spring 2028
- Available for a Summer 2027 internship (May/June start dates) in San Francisco Or New York.
- Prior research experience or a track record of publications on LLMs, NLP, multimodal models, agents, safety, evaluation, alignment, or a related field
- Experience with one or more general purpose programming languages, including Python, Javascript, or similar
Skills
Benefits
- comprehensive health, dental and vision coverage
- retirement benefits
- a learning and development stipend
- generous PTO
- may be eligible for a commuter stipend
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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