Anyone AI

Role Description Anyone AI is recruiting skilled Full-Stack Developers to work on a project with a leading AI lab. Contributors will design and evaluate realistic software engineering tasks, including: - Bug resolution - Feature implementation - Refactoring/migration - Test generation This is a project-based consultant role. Consultants will be paid on a per-project basis; hourly rates are estimates based on anticipated completion time. Consultants control their own schedule, provide their own tools, and may simultaneously provide services to other vendors/employers (subject to those vendors’ allowances). Qualifications - Advanced professional written proficiency in English - 3–7 years of professional software engineering experience - Strong proficiency in Python and JavaScript/TypeScript; working knowledge of Java, C#, or Go - Backend or full‑stack development experience in production systems - Experience with testing frameworks (e.g., pytest, Jest, JUnit, xUnit, Go testing) - Proven ability to debug and navigate large, multi‑file codebases - Experience with code reviews, refactoring, and production migrations Responsibilities - Design and implement multi-file coding tasks across bug fixing, feature development, refactoring, and testing - Write clear natural-language specifications and reference implementations - Develop and extend unit and integration test suites - Review peer-generated tasks for correctness, clarity, and realism - Identify edge cases, ambiguities, and potential failure modes - Ensure alignment between specifications, code, and expected outputs Expected Outcomes - High-quality, production-realistic coding tasks - Complete and correct reference implementations - Robust test coverage and validation artifacts - Structured, actionable peer review feedback Work Type - Remote - Part-time, project-based expert evaluation work

• Support cross-functional teams (admissions, career, placement, billing) with data and automation needs. • Design and maintain automation workflows with Zapier, Typeform, Hubspot, AppScripts, Notion/Airtable, and external APIs. • Build and maintain BI dashboards (Looker Studio, Google Sheets). • Use lightweight database solutions (e.g., Supabase) to structure and sync data across internal processes.

• Evaluation research. Turn public benchmarks and eval targets into original evaluation designs. Own the hard questions: construct validity, discrimination, headroom, and contamination. • Benchmark development. Build evaluation packages with subject-matter experts, each with expert-verified ground truth, multi-model headroom results, and rigorous QC (calibration layers, severity-weighted rubrics, deterministic verifiers). • Experts. Recruit, calibrate, and review a pool across coding, agentic/tool-use, and STEM/reasoning. Be the final arbiter of correctness and frontier difficulty. • Lab relationships. Be a technical point of contact for labs, with CEO support. Understand what they're trying to measure and translate it into an evaluation design. • Delivery. Turn lab requests into winning sample packages, then own pilots end to end. Nothing ships before it's lab-ready.

Role Description Anyone AI is recruiting skilled Python Developers to work on a project with a leading AI lab. Contributors will design and evaluate realistic software engineering tasks, including: - Bug resolution - Feature implementation - Refactoring/migration - Test generation This is a project-based consultant role. Consultants will be paid on a per-project basis; hourly rates are estimates based on anticipated completion time. Consultants control their own schedule, provide their own tools, and may simultaneously provide services to other vendors/employers (subject to those vendors’ allowances). Qualifications - Advanced professional written proficiency in English - 3–7 years of professional software engineering experience - Strong proficiency in Python and JavaScript/TypeScript; working knowledge of Java, C#, or Go - Backend or full‑stack development experience in production systems - Experience with testing frameworks (e.g., pytest, Jest, JUnit, xUnit, Go testing) - Proven ability to debug and navigate large, multi‑file codebases - Experience with code reviews, refactoring, and production migrations Responsibilities - Design and implement multi-file coding tasks across bug fixing, feature development, refactoring, and testing - Write clear natural-language specifications and reference implementations - Develop and extend unit and integration test suites - Review peer-generated tasks for correctness, clarity, and realism - Identify edge cases, ambiguities, and potential failure modes - Ensure alignment between specifications, code, and expected outputs Expected Outcomes - High-quality, production-realistic coding tasks - Complete and correct reference implementations - Robust test coverage and validation artifacts - Structured, actionable peer review feedback

• Design and implement multi-file coding tasks across bug fixing, feature development, refactoring, and testing • Write clear natural-language specifications and reference implementations • Develop and extend unit and integration test suites • Review peer-generated tasks for correctness, clarity, and realism • Identify edge cases, ambiguities, and potential failure modes • Ensure alignment between specifications, code, and expected outputs

• Design and implement multi-file coding tasks across bug fixing, feature development, refactoring, and testing • Write clear natural-language specifications and reference implementations • Develop and extend unit and integration test suites • Review peer-generated tasks for correctness, clarity, and realism • Identify edge cases, ambiguities, and potential failure modes • Ensure alignment between specifications, code, and expected outputs

• Design and implement multi-file coding tasks across bug fixing, feature development, refactoring, and testing • Write clear natural-language specifications and reference implementations • Develop and extend unit and integration test suites • Review peer-generated tasks for correctness, clarity, and realism • Identify edge cases, ambiguities, and potential failure modes • Ensure alignment between specifications, code, and expected outputs

• Design and implement multi-file coding tasks across bug fixing, feature development, refactoring, and testing • Write clear natural-language specifications and reference implementations • Develop and extend unit and integration test suites • Review peer-generated tasks for correctness, clarity, and realism • Identify edge cases, ambiguities, and potential failure modes • Ensure alignment between specifications, code, and expected outputs

• Design and implement multi-file coding tasks across bug fixing, feature development, refactoring, and testing • Write clear natural-language specifications and reference implementations • Develop and extend unit and integration test suites • Review peer-generated tasks for correctness, clarity, and realism • Identify edge cases, ambiguities, and potential failure modes • Ensure alignment between specifications, code, and expected outputs

• Design and implement multi-file coding tasks across bug fixing, feature development, refactoring, and testing • Write clear natural-language specifications and reference implementations • Develop and extend unit and integration test suites • Review peer-generated tasks for correctness, clarity, and realism • Identify edge cases, ambiguities, and potential failure modes • Ensure alignment between specifications, code, and expected outputs