Puzzle Solver (Coding)
About The Position
We are looking for highly skilled coding puzzle solvers to contribute to an AI training project involving algorithmic reasoning, debugging, constrained technical problems, and reproducible software solutions. The work involves solving self-contained coding and technical challenges designed to test the capabilities of advanced AI models. A representative task may require exploring an unfamiliar codebase or terminal environment, understanding a precise objective, implementing a solution, testing it against hidden or explicit constraints, and producing a reproducible final result.
Requirements
- Strong algorithmic problem-solving ability.
- Proficiency in at least one general-purpose programming language, such as C++, Python, Java, Rust, Go, C#, JavaScript, or TypeScript.
- Strong understanding of common data structures and algorithms.
- Ability to reason carefully about constraints, complexity, edge cases, and correctness.
- Experience debugging unfamiliar code or solving technically ambiguous problems.
- Ability to work independently in terminal-based development environments.
- Ability to produce reproducible, testable software solutions.
- Clear written and verbal technical communication.
Nice To Haves
- A public or otherwise verifiable Codeforces profile demonstrating meaningful competitive-programming experience is nice to have.
Responsibilities
- Solve self-contained coding, logic, debugging, and technical reasoning challenges.
- Analyze unfamiliar problems and translate their requirements into implementable solutions.
- Select appropriate algorithms, data structures, and problem-solving strategies.
- Work inside terminal-based development environments and existing codebases.
- Implement correct and efficient solutions using an appropriate programming language.
- Identify ambiguous requirements, edge cases, hidden assumptions, and failure conditions.
- Debug incorrect behavior across code, tests, dependencies, and environment configuration.
- Develop tests and verification methods that distinguish genuinely correct solutions from superficially plausible ones.
- Review AI-generated solutions and identify logic errors, incomplete reasoning, and constraint violations.
- Produce clear, reproducible solutions that can be executed and evaluated automatically.
- Explain reasoning, implementation decisions, and trade-offs clearly
Benefits
- Compensation is output-based. Experts are paid per task that meets the project specifications.
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What This Job Offers
Job Type
Part-time
Career Level
Mid Level
Education Level
No Education Listed
