Research Intern

The Voleon Group•Berkeley, CA

About The Position

Voleon is a technology company that applies state-of-the-art AI and machine learning techniques to real-world problems in finance. For nearly two decades, it has worked at the frontier of applying AI and machine learning to investment management and has become a multibillion-dollar asset manager. As a Research Intern, you will work directly with machine learning scientists, statisticians, and technical innovators. You will apply modern statistical machine learning research to large, high-dimensional data sets and contribute to work with an enduring impact on the field. The role involves research and technical work spanning data preparation, model development, and production software implementation, including development of predictive models and components of automated trading systems. Voleon describes its working environment as enriching and collegial and offers competitive compensation and benefits, expert technology talks, a modern office, and daily catered lunches. The Voleon Group is an Equal Opportunity Employer.

Requirements

Be a current graduate student in a quantitative discipline, expecting to attain a Ph.D. in December 2026 or during 2027.
Have a background in modern statistical methods and machine learning.
Have key contributions to multiple top-tier publications.
Have programming experience and an interest in software development techniques.
Be authorized to work in the United States.
Have an essential interest in financial applications; prior finance experience is not a primary factor in hiring.

Responsibilities

Work on complex problems with a research team whose members have published academic articles in top-tier venues on machine learning, systems, and theory.
Apply expertise in a technical field such as statistics, mathematics, computer science, engineering, or operations research to challenging problems.
Develop predictive models and other components of automated trading systems.
Work across data preparation, model development, and production software implementation.