Data Engineer for AI Model Evaluation

This position offers a unique opportunity to contribute to a cutting-edge AI research project focused on enhancing frontier AI coding models. As a data engineer, you will engage in structured technical assessments to evaluate and improve coding agents, working within realistic data engineering workflows.

• Utilize frontier AI coding agents to complete and assess complex data engineering tasks.
• Review model-generated implementations, including ETL pipelines, data warehouses, analytics platforms, and distributed data systems.
• Identify bugs, edge cases, scalability issues, and potential failure modes.
• Compare outputs from various frontier models and evaluate their strengths and weaknesses.
• Apply professional engineering judgment to realistic data engineering scenarios.

This is a sprint-based project with tasks running in 12-24 hour stretches, depending on client requirements.

Compensation is $400 per accepted task, with typical tasks taking approximately 2, 3 hours after ramp-up. Payment is directly tied to accepted work.

• Minimum of 2 years of professional data engineering experience.
• Experience in building ETL pipelines, data warehouses, analytics platforms, or distributed data systems.
• Regular use of AI coding agents such as Cursor, Claude Code, Codex, Windsurf, Gemini CLI, or similar tools.
• Ability to evaluate model-generated data infrastructure and pipeline implementations.
• Experience with large-scale data platforms is preferred.