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This position was posted on April 17, 2026 and is likely no longer accepting applications. We've kept it here for historical reference. Check out the similar jobs below!
Job Overview
Location
Austin
Job Type
Contract
Category
Software Engineering
Date Posted
April 17, 2026
Full Job Description
š Description
- ā¢ Help train large language models (LLMs) to write production-grade code by comparing, ranking, and refining AI-generated code snippets across multiple programming languages, directly influencing how AI learns to produce reliable, efficient, and secure software.
- ā¢ Day-to-day responsibilities include evaluating code quality, identifying logic errors and performance issues, providing detailed written feedback, and injecting that feedback into the RLHF (Reinforcement Learning from Human Feedback) pipeline to improve model behavior.
- ā¢ Work with G2i Inc., a remote-first company connecting skilled developers with meaningful projects, where your expertise in TypeScript and code review directly contributes to advancing AI-assisted software development.
- ā¢ Develop deep expertise in AI code evaluation, refine your ability to articulate technical trade-offs, and gain hands-on experience shaping the future of generative AI in software engineering ā all while working autonomously in a flexible, asynchronous environment.
Skills & Technologies
See exactly how your profile matches this role ā strengths, skill gaps, and what to do about them.
About G2i Inc.
G2i is a technical talent marketplace that pre-vets React, React Native, and Node.js engineers for U.S. companies. Founded by developers to solve hiring pain, it runs extensive code reviews, pair-programming interviews, and background checks before matching engineers for contract or full-time remote roles. G2i emphasizes mental health, offering a monthly wellness stipend and a zero-burnout policy. The company also provides direct-hire services and manages payroll, compliance, and ongoing support, enabling startups and enterprises to scale engineering teams quickly while maintaining code quality and developer well-being.
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