Mindrift

Competitive Programming Expert - Freelance AI Trainer

Mindrift
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1 day ago
Remote, RomaniaSenior

Responsibilities

  • Write original algorithmic problems with clear statements, sound constraints, and intended solutions.
  • Write correct solutions in C++ and Python.
  • Create realistic incorrect solutions that represent common 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.

Requirements

  • Strong competitive-programming background demonstrated by a public profile, Codeforces rating, or IOI, ICPC, or national-olympiad record.
  • Fluent contest-level C++ knowledge, including STL and complexity analysis.
  • Comfort writing Python.
  • Ability to explain why solutions are incorrect and create inputs that expose their failures.
  • Strong written English at C1+ level.
  • Applicants should provide competitive-programming handles and ratings, problem-setting experience, and IOI/ICPC/olympiad history.
  • Experience setting or testing problems for contests, using testlib, or creating LLM code-benchmark or evaluation datasets 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, with no guaranteed workload.
  • Payment is made per accepted task, with rates dependent on qualification tier and efficiency, up to the equivalent of $90/hr.

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Mindrift

About Mindrift

1,001-5,000 employees

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.

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