Machine Learning Research Intern (Summer 2027)
Scale AI · New York, NY; San Francisco, CA
About this role
**Machine Learning Research Intern (Summer 2027) — Scale** ## About the role At Scale, our mission is to develop reliable AI systems for the world’s most important decisions. Our Machine Learning Research team builds the foundation for the next generation of AI systems—pushing the boundaries of frontier models while ensuring safety, reliability, and alignment. As an intern, you’ll work on a combination of deeply technical ML applications in production and cutting-edge research problems, with mentorship from world-class researchers. Interns own real, published or shipped work—not side projects. ## Example projects - 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 requiring 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 - Improve production models via retraining and hyperparameter searches, then deploy without regressing core model characteristics - Create post-training or agentic solutions that integrate into delivering applications for enterprise and public sector clients ## Required to have - Currently enrolled in a BS, MS, or PhD program focused 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) 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 ## Ideally you’d have - A previous internship in ML/DL/NLP, adversarial robustness, alignment, evaluation, or agents - Experience as a researcher (internships, full-time roles, or a lab) - Publications at top-tier venues (e.g., NeurIPS, ICML, ICLR, CVPR, ACL, EMNLP, AAAI) or contributions to open source - Hands-on experience with reinforcement learning, agentic systems, or evaluation infrastructure ## How we work (credos) - **Earn Customer Love** - **Team Flow** - **Quality is Our Cheat Code** - **Find the 20%** - **Write the Market** - **Three Moves Ahead** ## Compensation & benefits (pay transparency) Compensation packages for eligible roles include base salary, equity, and benefits. For this role, the base salary range in **San Francisco and New York** is **$120,000–$150,000 USD** (determined during the interview process based on location and other factors). Benefits may include comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO (and possibly a commuter stipend). ## Notes - Scale’s policy requires a **90-day waiting period** before reconsidering candidates for the same role. - Scale is an inclusive, equal opportunity workplace and provides reasonable accommodations.
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