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Machine Learning Research Intern (Summer 2027)

Scale AI · New York, NY; San Francisco, CA

Posted Oct 19, 2026

Est. total comp~$40/hr

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From the posting

At Scale , 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 & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force.

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.

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.

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. …

Excerpt from Scale AI's public job board. Read the full posting.

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Named in the posting 7 items

Education: Enrolled in or recently finished a phd program

Skills and tools: Python, Java, JavaScript, Machine learning, Deep learning, Excel

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About this listing. Pulled automatically from Scale AI's public job board and refreshed daily; closed roles are removed. Mars Mining Co. is not the employer, does not take applications and does not screen candidates. Field and level labels come from the job title and can be wrong.

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About the pay figures (~): These are estimates. Yearly figures are estimated total comp ranges: the employer's posted pay range, or, with no posted pay, the median to 90th-percentile BLS wage for similar jobs, plus typical benefits and bonus, without stock. Hourly figures for internships and contract roles are posted rates or BLS hourly wage ranges. Figures outside the U.S. and for loosely matched titles are rough ballparks. How we estimate