Developed and led the deployment of advanced ML solutions for multimodal search, personalized recommendations, and AI-driven product tagging, optimizing engagement and revenue for large-scale e-commerce platforms. ● Architected and optimized multimodal search algorithms, integrating text and image embeddings to enhance product discovery, increasing conversion rates by 14%. ● Designed and implemented deep learning-powered recommendation systems, leveraging user behavior data to personalize product suggestions, boosting CTR by 12% and revenue per session by 8%. ● Developed and productionized GenAI-powered product tagging models, automating product classification and metadata enrichment, improving catalog navigation and search relevance. ● Optimized ML pipelines and large-scale data processing, reducing inference latency by 25% and scaling recommendation models to handle 10M+ daily queries across global platforms. ● Defined and led the ML roadmap, collaborating with product managers and engineers to drive AI adoption, enhance personalization strategies, and optimize A/B testing workflows for revenue impact.

● Increased YouTube Ads CTR by 18% through optimized audience segmentation. ● Automated ad performance forecasting, reducing A/B testing costs by 30%. ● Led regional marketing campaigns, driving engagement across CIS. ● Collaborated with Google Ads teams to enhance ML-driven ad targeting.