YBAI

Over 12 years of AI leadership and hands-on development across NLP, computer vision, and agentic workflows. Ex-Head of AI at Nielsen; built scalable AI products used by enterprise clients worldwide. Expertise spans LLMs (OpenAI, Claude, Gemini), prompt engineering, LangChain, multimodal agents, and real-time inference pipelines. I consult on architecture, PoC development, and AI-driven product strategy—from zero to production.

Over a decade of ML experience—from classic regression models to deep learning and ensemble systems. Designed and deployed ML pipelines for structured, unstructured, and multimodal data. Hands-on with sklearn, XGBoost, TensorFlow, PyTorch, and MLOps workflows (including SageMaker, Vertex AI, and on-prem). Proven impact in optimizing operations, personalizing user experiences, and automating decisions across tech, media, and enterprise domains.

Led CV projects from research to deployment, including real-time object detection, OCR, activity recognition, and video analytics at scale. Experience spans OpenCV, TensorFlow, YOLO, MediaPipe, and custom CNNs. Applied CV in production for enterprise workflows, retail analytics, smart surveillance, and developer screen understanding. Built systems integrating vision with LLMs and automation agents.

Extensive experience building NLP pipelines, from classic text processing to advanced transformer-based LLM applications. Worked on intent recognition, NER, summarization, embeddings, and custom prompt engineering. Deployed NLP systems in production across finance, media, and support ops. Hands-on with spaCy, Hugging Face, LangChain, OpenAI APIs, and hybrid search. Focused on precision, latency, and measurable ROI.

Over a decade of hands-on and leadership experience in building data-driven systems. Led end-to-end data pipelines—from raw ingestion to real-time dashboards and predictive modeling. Delivered business-critical insights using Python, SQL, Spark, and modern BI tools. Architected scalable solutions on cloud and on-prem for enterprise clients, including custom ML models, KPI frameworks, and big data processing workflows.