Own end-to-end production ML systems for search, recommendations, and ranking: architecture, training pipelines, inference, deployment, monitoring, drift detection, and retraining. Partner with data, product, and backend teams to ship reliable, low-latency ML-driven product experiences and set standards for ML infrastructure and model health.

Authenticate sneaker listings by verifying condition, details, and photos; remove unsafe or non-compliant listings; investigate defects; train and mentor team members; support process improvements and company OKRs; maintain up-to-date sneaker and counterfeit knowledge.