12 hours ago
Remote, Turkey +4 moreSenior
Responsibilities
- Write original competitive-programming problems with clear statements, sound constraints, and intended solutions.
- Write correct solutions in C++ and Python.
- Create realistic wrong solutions that represent common programming mistakes.
- Build generators, edge cases, stress tests, and hacking tests.
- Write testlib checkers and interactors for problems with multiple valid answers.
- Verify that correct solutions pass and incorrect solutions fail within time limits.
- Submit tasks by deadlines and meet project acceptance criteria.
Requirements
- Strong competitive-programming background demonstrated by a public profile with a qualifying Codeforces rating or IOI, ICPC, or national-olympiad achievement.
- Fluent contest-level C++ knowledge, including STL and complexity analysis.
- Comfort writing Python.
- Ability to explain why solutions are wrong and construct inputs that expose errors.
- Strong written English at C1+ level.
- 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 experience, and LLM code-benchmark or reinforcement-learning evaluation dataset experience are preferred.
Benefits
- Remote work from Israel.
- Part-time, project-based freelance participation rather than permanent employment.
- Estimated workload of 10–20 hours per week during active project phases, with no guaranteed workload.
- Tasks are completed after qualification and project assignment and are paid per accepted task.
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.