Machine Learning Engineer

Tasty

United States

United States

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About

We're building an internal visual classification system that can analyze photos and videos and automatically tag them across 70+ content categories. This is a full-time role. Open to LA-based or remote. Competitive comp. The foundation is there. we're working with existing vision APIs. but we need someone who can make the system actually work at the level we need. That means integrating the API, tuning and calibrating it against our specific taxonomy, building the processing pipeline around it, handling edge cases, and ensuring classification accuracy stays high as we scale. What you'd be doing:
Integrating and configuring vision APIs for multi-label classification across 70+ categories Fine-tuning and calibrating model outputs to match our specific content taxonomy Building the end-to-end pipeline ingestion, processing, tagging, and validation Monitoring accuracy, identifying failure patterns, and continuously improving results Building tooling to make it easy for the team to review, correct, and refine classifications
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United States

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English

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