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Opportunity for software developers, founders, engineering teams, and code owners to submit existing repositories for licensing evaluation. Eligible code includes abandoned startups, personal projects, internal tools, SaaS products, and discontinued applications. Applicants must own or legally control the code and exclude unauthorized third-party material. Compensation is based on agreed licensing terms, with reference rates for non-exclusive licensing.

Build realistic backend coding challenges, feature implementations, bug fixes, and deterministic verifiers for AI training projects. Evaluate code correctness, reliability, maintainability, and performance while incorporating automated testing, validation criteria, edge-case analysis, and secure coding practices. Work independently on scalable backend systems and APIs, refine tasks based on requirements, and document technical solutions clearly.

Debug and improve software across diverse codebases, identify and remediate vulnerabilities, conduct security audits and penetration testing, refactor legacy systems, optimize backend applications, and document technical findings. The role contributes cybersecurity and software engineering expertise to AI training datasets while working independently on project-defined tasks.

Research fellows will validate AI-generated paper reproductions, simulations, and results; map research areas; define standards for high-quality AI research; create benchmark tasks and evaluations; and contribute as lead or first authors to a public benchmark paper and evaluation release.

Review, label, classify, and validate data used to train and evaluate Gemini. Apply detailed guidelines consistently, identify discrepancies and edge cases, perform quality checks, escalate unclear cases, and provide feedback while meeting productivity and accuracy standards in a remote contract role.

Research Fellows will validate AI-generated paper reproductions, simulations, and results; map research taxonomies; define standards for high-quality AI-assisted science; and create benchmark tasks and evaluations for frontier AI models. Fellows will contribute to a publicly released benchmark paper and open evaluation set as lead or first authors. The contract offers flexible, remote global work for current STEM PhD students or postdocs with published research and hands-on AI agent experience.

Review, label, classify, and validate data used to train and evaluate Gemini. Apply detailed guidelines consistently, identify edge cases and annotation issues, perform quality checks, escalate unclear cases, and provide feedback. This is a short-term remote freelance contract requiring 40 hours weekly, including PST overlap. Candidates must be U.S.-based, eligible for 1099 contracting, students or recent graduates, experienced with at least 20 recent Gemini chat sessions, and comfortable sharing Gemini history.