At Confidential (Registered Users Only), we believe advanced research belongs in production, driving core algorithmic advances at a global scale. Machine Learning is a key growth lever, powering everything from real-time 3D generative AI to complex ecosystem economics across our global platform. As an Applied Scientist - PhD Intern, you’ll be part of a community of curious scientists and engineers building the foundational and applied ML methods at a scale of millions of daily active users and billions of daily AI requests. We combine innovative research—including Computer Vision and Graphics, multimodality, NLP, and recommendation systems—with world scaling distributed engineering.
During your 12 or 16 week internship in the Winter, Summer, or Fall, you’ll own a high-impact project from ideation and experimentation to production and publication. There’s also the possibility of continued collaboration beyond your internship, as we support experimentation and production with top researchers, engineers, faculty, and PhD candidates globally that can lead to publications at esteemed venues.
You Will
- Prototype, experiment with, and deploy advanced AI, machine learning, and 3D technologies to solve real-world challenges at scale.
- Translate cutting-edge research into production-ready features alongside our community of curious, cross-functional engineering and product teams.
- Develop, deliver, and optimize solutions that measurably enhance user experience, safety, and creativity on our platform.
You Have
- Possess or are pursuing a PhD in computer science, engineering, or a related field, with a thesis aligned to Confidential (Registered Users Only)’s research areas.
- Deep expertise in a relevant technical domain, including deep learning, computer vision, NLP, reinforcement learning, or distributed systems.
- Proficiency in one or more programming languages (e.g., Python, C++, Go, Java) with experience building and optimizing large-scale systems.
- A strong research track record, evidenced by multiple publications and presentations in highly regarded peer-reviewed venues.
You may redact age, date of birth, and dates of attendance/graduation from your resume.