Software Engineer (Open Source Contributor)

This role is for one of our clients Pay: 50-100/hour Role Type: Contractor Location: Anywhere in the world, remote Estimated Time Commitment: Approximately 15 hours per task run Start Timeline: Within 24-48 hours of onboarding We are seeking experienced Software Engineers and Open Source Contributors to help develop and evaluate next-generation AI systems through high-quality software engineering tasks. This opportunity is ideal for developers with strong programming fundamentals, practical experience contributing to open-source projects, and a proven ability to solve complex engineering problems. In this role, you will design realistic, challenging, and reproducible coding environments that assess an AI model's ability to fix bugs, implement new features, refactor existing code, and optimize software performance. You will also develop reliable verification mechanisms and golden reference solutions to evaluate whether AI-generated code meets the specified requirements. Prior experience in artificial intelligence is not required. Your software engineering expertise, code quality standards, debugging skills, and open-source contributions will be central to the role. Requirements Key Responsibilities Coding Task Development: Create realistic, technically challenging programming tasks involving bug fixes, feature development, code refactoring, and performance optimizationReproducible Environment Setup: Build deterministic reinforcement learning environments with the necessary dependencies, test suites, configurations, and execution instructionsReference Solution Implementation: Develop reliable golden reference solutions that demonstrate the expected behavior and satisfy all task requirementsAutomated Verification: Design deterministic evaluators and test cases that accept valid implementations while rejecting incorrect, incomplete, or non-compliant solutionsSoftware Debugging: Investigate complex software defects, troubleshoot unexpected behavior, and resolve performance bottlenecks across diverse codebasesFeature Engineering: Implement robust and scalable features while following established software development principles and coding standardsCode Refactoring and Optimization: Improve existing codebases by enhancing readability, maintainability, execution efficiency, and long-term reliabilityCode Review and Validation: Review code contributions and technical submissions for correctness, clarity, performance, and adherence to best practicesTechnical Documentation: Document problem statements, implementation decisions, debugging strategies, testing procedures, and solution reasoning to support high-quality AI training and evaluationContinuous Improvement: Refine tasks and evaluation criteria based on observed model behavior and identified weaknesses Required Qualifications Strong software engineering experience in one or more programming languages, including Python, Java, C++, Go, Rust, or TypeScriptDemonstrated experience developing backend systems, scalable services, APIs, or complex software applicationsA clear track record of open-source contributions, preferably supported by a GitHub profile or equivalent public portfolioStrong understanding of data structures, algorithms, software design principles, and debugging techniquesPractical experience with automated testing, code validation, and software quality assuranceAbility to identify and resolve complex bugs, implementation errors, and performance bottlenecksExperience developing new features and improving existing codebasesStrong analytical thinking, problem-solving, documentation, and technical communication skillsAbility to work independently, follow detailed technical specifications, and deliver reproducible, verifiable solutionsInterest in AI systems and understanding how software engineering expertise can support AI model training and evaluation Must-Have Skills Software EngineeringOpen Source ContributionsBackend Development and API DesignPython, Java, C++, Go, Rust, or TypeScriptDebugging and TroubleshootingData Structures and AlgorithmsAutomated Testing and Code ValidationCode Review and RefactoringPerformance Optimization Good-to-Have Skills Experience with large-scale or legacy codebasesReinforcement Learning Environment DevelopmentDeterministic Testing and Automated EvaluationCI/CD and Development ToolingScalable Distributed SystemsPerformance Profiling and OptimizationComplex Feature ImplementationAI Model Evaluation and Coding Agent AssessmentPublic GitHub repositories or notable open-source projects Opportunity Snapshot Time Commitment: Approximately 15 hours per task run, depending on complexity and individual workflowFlexible Schedule: Work with flexibility while meeting task requirements and weekly submission minimumsGetting Started: Selected candidates receive onboarding instructions and the resources required to beginPortfolio Requirement: A public GitHub profile or another portfolio demonstrating relevant open-source contributions is preferredAlternative Assessment: Candidates whose public portfolios do not sufficiently demonstrate their skills may be required to complete a HackerRank technical assessmentCompensation: Payment is based on completed tasks that meet the specified quality and acceptance criteria Selection Process Application: Submit your application and complete the initial screening questionsAI Interview: Complete an approximately 20-minute interview focused on your technical experience and problem-solving approachTechnical Assessment: Complete a HackerRank assessment if your portfolio does not adequately demonstrate the required expertiseHiring Manager Review: Your application, technical capabilities, and assessment results will be reviewedOnboarding: Selected candidates receive onboarding materials and instructions for beginning their assignments Candidates are expected to complete interviews and assessments independently so their technical judgment and problem-solving abilities can be evaluated accurately. Expected Availability The selection process may move quickly, with positions often filled within approximately 48 hours. Successful candidates should be prepared to begin their first tasks within 24-48 hours after completing onboarding.