Sr. SWE for Code Reviewing LLM Data Training (C#)

Who you are

You have 5–7+ years of experience in C# development, QA, or code review — your deep expertise in C# syntax and the .NET framework allows you to assess code functionality and security effectively. You are comfortable using debugging tools and code execution environments, ensuring that you can validate code snippets accurately. Your strong written communication skills enable you to provide clear and constructive feedback to annotators, helping maintain high standards in AI training. You have experience working with structured QA processes and understand the importance of following strict quality guidelines.

Desirable

Experience with enterprise application development is a plus, as it gives you a broader perspective on code quality and functionality. Familiarity with various testing frameworks such as xUnit, NUnit, and MSTest will enhance your ability to evaluate code effectively.

What you'll do

In this role, you will review and audit evaluations completed by data annotators assessing AI-generated C# code responses. Your primary responsibility will be to ensure that the C# code adheres to prompt instructions and is functionally correct. You will validate code snippets using proof-of-work methodology, identifying inaccuracies in annotator ratings or explanations. Providing constructive feedback will be crucial to maintaining high annotation standards and ensuring that all evaluations meet the required quality guidelines. You will work within Project Atlas guidelines, focusing on evaluation integrity and consistency throughout the process.

What we offer

G2i Inc. connects subject-matter experts with flexible, remote AI training opportunities, ensuring consistent and reliable compensation for your contributions. You will have the opportunity to work on innovative projects that contribute to the advancement of AI technologies. Compensation is personalized based on your experience level, educational background, location, and industry expertise, ensuring that you are rewarded fairly for your skills and contributions. We encourage you to apply even if your experience doesn't match every requirement, as we value diverse backgrounds and perspectives.