Machine Learning Research Intern (Summer 2027)

<p>At <strong>Scale</strong>, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst &amp; Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force.</p> <p>Scale's Machine Learning Research team builds the foundation for the next generation of AI systems — pushing the boundaries of what's possible with frontier models while ensuring safety, reliability, and alignment at every step. Our work spans generative AI, reinforcement learning and advanced post-training methods, scalable oversight, synthetic data pipelines, red teaming, and evaluation science.</p> <p>We are developing a large-scale hybrid human-machine system to power machine learning pipelines for dozens of industry-leading customers. These models and systems form the backbone of Scale's long-term strategy, enabling billions of tasks monthly and supporting some of the most complex and advanced use cases in the AI ecosystem.</p> <p>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 and the opportunity to collaborate with leading teams across industry and academia. Interns own real, published or shipped work — not side projects.</p> <h2><strong>Example Projects</strong></h2> <ul> <li>Measure the dangerous capabilities of frontier models and conduct preparedness research</li> <li>Research the science and creation of new benchmarks for frontier models</li> <li>Develop new methods for training models to excel on extremely difficult reasoning problems that require long chains of thought</li> <li>Research reinforcement learning and post