Built LLM fine-tuning pipelines (LoRA, QLoRA, PEFT), RAG with LangChain/LlamaIndex/FAISS, multimodal OCR+ViT+GPT, synthetic data with StyleGAN, and deployed on GCP Vertex AI and Azure OpenAI. Implemented MLOps, monitoring, and analytics.

Designed and deployed LLM-based RAG architectures, multimodal AI pipelines, and scalable ML systems on GCP/Azure. Led team of 6+ AI engineers and improved incident response efficiency by 45%.

Developed ML models (XGBoost, LightGBM, CatBoost), time-series forecasting, computer vision pipelines, OCR+NER, explainable AI dashboards, and automated CI/CD with Kubeflow and Airflow.

Delivered ML models for fraud detection and CLV, real-time inference APIs with Docker/Kubernetes, and automated CI/CD ML pipelines. Reduced latency by 35% and accelerated release cycles 3x.

Designed A/B testing, clustering, NLP pipelines (Naive Bayes, TF-IDF, Word2Vec), visual analytics with Tableau, and blockchain data analytics. Collaborated with stakeholders and translated AI insights.

Automated A/B testing frameworks, customer segmentation, and NLP solutions for ticket routing and email classification. Built analytics dashboards for executive decision-making.