Nonprofit
USIOT Competitive Programming Problem Setter
Details
Description
The United States Informatics Olympiad in Teams (USIOT) is seeking volunteer problem setters to help develop original algorithmic programming problems for the 2026–2027 competition season.
Problem setters will work with the USIOT problem-setting team to design, test, and prepare problems for online qualification rounds and the USIOT National Finals. This is a remote volunteer position.
Responsibilities may include:
- Proposing original competitive programming problems and problem concepts
- Writing clear problem statements, input/output specifications, and constraints
- Developing official solutions and solution explanations
- Creating generators, test data, validators, and checkers where needed
- Estimating problem difficulty and helping build balanced contest problem sets
- Reviewing and testing problems written by other setters
- Participating in problem discussions and revisions before each contest
- Keeping unreleased problems and contest materials confidential
We are looking for volunteers with a strong background in algorithms, data structures, and competitive programming. Experience with competitions such as USACO, ICPC, Codeforces, AtCoder, or similar contests is especially helpful. Previous problem-setting experience is welcome but is not required.
Problem setters should be comfortable writing correct and efficient code in at least one common competitive programming language, such as C++, Python, or Java. Strong attention to detail is important, particularly when checking edge cases, constraints, and solution correctness.
The time commitment is flexible and varies throughout the season. Setters may contribute to one contest or remain involved across multiple rounds. Work is completed remotely, with coordination through the USIOT organizing team.
This is a volunteer opportunity and is well suited for experienced competitive programmers who want to contribute to a national programming competition and gain experience designing and evaluating algorithmic problems.
