1 day ago
Remote, India +5 moreSenior
Responsibilities
- Write original algorithmic problems with clear statements, sound constraints, and intended solutions.
- Implement correct solutions in C++ and Python.
- Create realistic incorrect solutions that represent common programming mistakes.
- Build generators, edge cases, stress tests, and hacking tests.
- Write checkers and interactors with testlib for problems with multiple valid answers.
- Validate that correct solutions pass and incorrect solutions fail within time limits.
Requirements
- Demonstrated competitive-programming strength through a public profile, qualifying Codeforces rating, or IOI, ICPC, or national-olympiad achievement.
- Fluent contest C++ skills, including STL and complexity analysis, plus comfort writing Python.
- Ability to explain why solutions are incorrect and construct inputs that expose their flaws.
- Strong written English at C1+ proficiency.
- Applicants should provide competitive-programming handles and current or peak ratings, problem-setting experience, and IOI/ICPC/olympiad history.
- Experience setting or testing problems for contests, Testlib checkers/validators/generators, or creating LLM code-benchmark and evaluation data is preferred.
Benefits
- Remote, part-time, project-based freelance work rather than permanent employment.
- Estimated workload of approximately 10–20 hours per week during active project phases, subject to project requirements.
- Flexible project workflow involving qualification, project participation, task completion, and acceptance-based payment.
- Tasks must meet stated deadlines and acceptance criteria.
About Mindrift
Mindrift builds an expert-sourcing platform that connects domain specialists to project-based work training and evaluating generative AI models, including supervised fine-tuning, RLHF, evaluation, and red-teaming. It is built and operated by Toloka, part of Nebius Group, and run from Amsterdam, Netherlands. Work is fully remote and freelance, serving global technology companies developing and improving large AI systems.