AI/ML Engineer — Classification + Matching

Що робити

• Build a classification pipeline that flags paid vs. non-paid endorsements and categorizes endorsement type per our specification
• Build brand matching (entity resolution) against our database using fuzzy and/or semantic matching, with a "suggest a new brand" fallback when nothing matches
• Use our labeled examples to train and/or tune the system, and set up an evaluation framework so we can measure and improve performance per task
• Process large volumes of entries efficiently and cost-effectively
• Document the approach and hand off a maintainable system