AI Model Training Dataset Creation - Code Evaluation & Bug Detection
Internal Proprietary ToolingTextRLHFComputer Programming Coding
Collaborated with Shipd (Y Combinator W24) to develop sophisticated training datasets for LLM capability testing. Created subtle code variations and intentional bugs designed to challenge AI model reasoning and improve detection accuracy. Annotated over 1,000 code samples with quality labels, edge case identification, and complexity scoring. Developed evaluation pipelines to measure model performance on nuanced programming tasks. Project required deep understanding of software engineering principles and AI model training methodologies.
Collaborated with Shipd (Y Combinator W24) to develop sophisticated training datasets for LLM capability testing. Created subtle code variations and intentional bugs designed to challenge AI model reasoning and improve detection accuracy. Annotated over 1,000 code samples with quality labels, edge case identification, and complexity scoring. Developed evaluation pipelines to measure model performance on nuanced programming tasks. Project required deep understanding of software engineering principles and AI model training methodologies.
2025 - 2025