Software Engineer, AI — Code Evaluation & Training (Remote)
Help train large-language models (LLMs) to write production-grade code across a wide range of programming languages:
Compare & rank multiple code snippets, explaining which is best and why.
Repair & refactor AI-generated code for correctness, efficiency, and style.
Inject feedback (ratings, edits, test results) into the RLHF pipeline and keep it running smoothly.
End result: the model learns to propose, critique, and improve code the way you do.
RLHF in one line
Generate code ➜ expert engineers rank, edit, and justify ➜ convert that feedback into reward signals ➜ reinforcement learning tunes the model toward code you’d actually ship.
4+ years of professional software engineering experience in one or more of the following:
Python, Java, JavaScript, TypeScript, Go, C++, PHP, COBOL, C, Ruby, or Rust.
(Constraint programming experience is a bonus but not required for all languages.)
Strong code-review instincts—you can spot logic errors, performance traps, and security issues quickly.
Extreme attention to detail and excellent written communication skills.
Much of this role involves explaining why one approach is better than another. This cannot be overstated.
You enjoy reading documentation and language specs and thrive in an asynchronous, low-oversight environment.
No prior RLHF (Reinforcement Learning with Human Feedback) or AI training experience.
No deep machine learning knowledge. If you can review and critique code clearly, we’ll teach you the rest.
We are looking for engineers with strong command of at least one of the following languages:
Python, Java, JavaScript, TypeScript, Go, C++, PHP, COBOL, C, Ruby, or Rust.
Location: Fully remote — work from anywhere
Compensation: Up to $30/hr
Hours: Minimum 15 hrs/week, up to 40 hrs/week available
Engagement: 1099 contract
Straightforward impact, zero fluff. If this sounds like a fit, [apply here].
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Seeking a detail-oriented Software Engineer with AI expertise to enhance large-language models for code generation in a fully remote environment.
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