Design, build, and validate ML/DL models across diverse domains(computer vision, NLP, predictive analytics, anomaly detection)
Oversee and drive the full model lifecycle: problem framing, data engineering, experimentation, evaluation, and deployment – collaborating with engineers and analysts for implementation
Apply rigorous statistical methods, hypothesis testing, and feature engineering to produce production‑quality models
Monitor deployed AI models against KPIs; detect performance drift and trigger calibration, re‑training, or architectural updates
Benchmark models and deliver structured evaluation reports to technical and business stakeholders
Agentic AI & Generative AI Application
Develop and maintain LLM‑powered solutions including RAG pipelines, AI agents, and multi‑step tool‑calling workflows