AI/ML Data Operations
2024-2026•AI Ops & ML Infrastructure•Client: TalkingPoints
AI quality assurance, cost controls, evaluation frameworks
Message classification stewarded to production. Machine Translation Quality Estimation app for self-service evaluation. Cost safeguards and visible tradeoffs.
Technology Stack
Snowflake AI CortexStreamlitPythonNLPdbt
Links
Frequently Asked Questions
How do you evaluate AI classification accuracy when ground truth is expensive?
Sample-based evaluation with human labeling. You can't label everything, but you can label enough to estimate accuracy and identify systematic errors. The key is choosing samples that are representative, not just convenient.
How do you balance AI capability with cost constraints?
Make the tradeoffs visible. Every AI feature has an accuracy level, a latency, and a cost per unit. Build dashboards that show all three. Let stakeholders decide what tradeoff they want, instead of making that decision invisibly in the engineering layer.