Summer 2027 Software Engineering Intern

PDT Partners•New York, NY

About The Position

PDT Partners, a quantitative investment manager, is seeking talented engineering students for Software Engineering focused internships. We are looking for interns who can add to a company that values creativity, energy, and collaborative problem solving. Throughout our 10-week program, students work closely with supportive senior developers on individual projects, receive hands-on personalized mentorship, and contribute to PDT's culture through both intern and company wide social events.

Requirements

Current Bachelor's, Master's, or PhD students pursuing degrees in rigorous, highly technical fields (e.g., Computer Science, Computer Engineering) who are eligible for full-time roles starting in 2028 or 2029.
Excellent academic background from a rigorous computer science or engineering program graduating in Fall 2027 or later.
Strong programming skills with a deep understanding of data structures and algorithms.
Fast-learner, intellectually curious, problem-solving approach.
Proactive with sense of urgency.
Strong verbal and written communication skills.
Interest in working in a world-class, professional environment.
Committed to improvement and keen to apply constructive feedback.

Responsibilities

Design, develop, debug, and test software components for large handling of financial data, real-time events, and batch processing.
Face problems that don't have well-defined solutions - creativity will be essential to come up with the best possible answers, including ones that explore new technologies.
Learn about financial markets and quantitative trading.
Build an understanding of various trading technologies and make contributions to them.
Develop tooling used for infrastructure management.
Contribute to the infrastructure and maintenance of large-scale data sets.
Apply new idioms, techniques, and algorithms in select areas, which may include program correctness (resource management, exception safety, reentrancy/thread safety), maintainability (portability, good coding practices, adherence to coding standards, unit testing, documentation), and efficiency (optimal data structures/algorithms, understanding of high-/low- level implications and trade-offs in design choices, parallelization).