AI Model Evaluation & Technical Annotation (Contract)
Conducted expert-level evaluation and technical annotation for AI coding agents in production open-source codebases. Rated model outputs, steered agentic coding sessions, and provided PR-level feedback to shape model training data and performance. Engineered Docker-based benchmarking pipelines and authored precise issue descriptions to optimize training signals and methodology quality.
• Evaluated agent outputs across seven code-grounded quality axes, with written rationales.
• Guided multi-turn agentic coding sessions, enforcing codebase and testing conventions.
• Developed benchmarking pipelines including test harnesses and patch validation.
• Improved agent failure analysis and documented reusable evaluation methodology.
Conducted expert-level evaluation and technical annotation for AI coding agents in production open-source codebases. Rated model outputs, steered agentic coding sessions, and provided PR-level feedback to shape model training data and performance. Engineered Docker-based benchmarking pipelines and authored precise issue descriptions to optimize training signals and methodology quality. • Evaluated agent outputs across seven code-grounded quality axes, with written rationales. • Guided multi-turn agentic coding sessions, enforcing codebase and testing conventions. • Developed benchmarking pipelines including test harnesses and patch validation. • Improved agent failure analysis and documented reusable evaluation methodology.
2025 - Present