Data Engineer for AI Model Evaluation
$80 per hourSaidGig
Help evaluate and improve frontier AI coding models by using AI coding agents to complete realistic data engineering tasks, then assess the outputs for correctness, scalability, and failure modes. Work centers on end-to-end data engineering workflows including ETL pipelines, data warehouses, analytics platforms, and distributed data systems.
Key Responsibilities- Use frontier AI coding agents to implement and test complex data engineering tasks.
- Review and validate model-generated code and configurations for ETL pipelines, data warehouses, analytics platforms, and distributed data systems.
- Identify bugs, edge cases, scalability bottlenecks, and failure modes in model outputs.
- Compare solutions produced by multiple frontier models and document relative strengths and weaknesses.
- Apply professional engineering judgment to realistic data infrastructure and pipeline scenarios, producing clear, actionable feedback.
- Minimum 2 years of professional data engineering experience.
- Hands-on experience 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 comparable tools.
- Ability to evaluate model-generated implementations of data infrastructure and pipelines.
- Experience operating large-scale data platforms is preferred.
- Location: Remote.
- Employment type: hourly.
- Sprint-based engagement, with work organized in 12 to 24 hour stretches based on client requirements.
- Spots are limited and assignments are filled on a first come, first serve basis.
- Metadata hourly rate: $80 per hour.
- Task-based pay: $400 per accepted task.
- Typical accepted tasks require approximately 2 to 3 hours of work after ramp-up.
- Payment is tied to accepted work, compensation is awarded only for tasks that meet acceptance criteria.
- Open to applicants who meet the listed qualifications.
- Because spots are limited, apply promptly; assignments are allocated on a first come, first serve basis.
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