We’re looking for experienced software engineers to build and evaluate Reinforcement Learning environments for AI models. You’ll create realistic software engineering challenges involving debugging, feature development, refactoring, and performance optimization, along with reproducible environments and reference solutions. Open-source contributions are required — applicants should have a GitHub/GitLab profile or other public work demonstrating strong coding ability. What You’ll Do Build complex coding challenges for AI models involving debugging, feature development, refactoring, and optimization. Develop expert-level solutions in Python, Java, Rust, Go, C++, or TypeScript. Analyze and resolve challenging bugs, performance issues, and code-quality problems. Create scalable, maintainable solutions following software engineering best practices. Document technical reasoning, approaches, and solution decisions. Review and validate technical submissions for correctness and quality. What We’re Looking For Strong hands-on experience in at least one supported programming language. Excellent knowledge of algorithms, data structures, and software engineering fundamentals. Proven experience debugging complex codebases and optimizing performance. Experience working with large or legacy codebases. Strong problem-solving, documentation, and communication skills. Public open-source contributions or a strong GitHub/GitLab profile. Interest in AI and emerging software engineering challenges is a plus; prior AI experience is not required.

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