Product intent to model targets
Translate "we want..." product goals into model behavior, latency targets, test scenarios, and release criteria.
AI R&D · Computer Vision · Model Lifecycle Delivery
I fine-tune, validate, and ship Vision AI.
I adapt Vision models for edge devices, validate accuracy and latency from model to solution level, and build feedback pipelines that turn real-world behavior into the next engineering cycle.
Edge-ready Vision systems
Adapt and validate Vision model variants so partner devices can run the experience reliably in real environments.
Field behavior to next iteration
Bring production findings back into the lab so Product, Data, and AI Engineering can improve the next release cycle.
Current focus
Practical QA for AI systems in the real world.
I combine six years of QA experience with a growing computer vision skillset to find product risks at the earliest stages of development.
Experience
Senior QA work across Vision Analytics, model testing, CI pipelines, and product delivery.
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