Nihar Paluvayi

About Nihar Paluvayi

I’m a Senior Data Scientist with 10+ years of experience building scalable AI, Machine Learning, and Generative AI solutions across Google, Intel, State Government, Banking, and Global Consulting environments.I specialize in designing and delivering end-to-end AI systems from business problem framing and KPI definition to production deployment, monitoring, and optimization. My work spans search systems, GenAI applications, industrial AI, risk modeling, and enterprise data platforms across GCP, Azure, and AWS.At Google, I focus on Generative AI and Search systems building Learning-to-Rank models, transformer-based NLP solutions, Retrieval-Augmented Generation (RAG) architectures, and Agentic AI workflows using Gemini and Vertex AI. I design scalable vector search pipelines, semantic retrieval systems, and autonomous reasoning frameworks that power intelligent search and conversational experiences.Previously at Intel, I led AI initiatives for semiconductor manufacturing, developing predictive maintenance, anomaly detection, and advanced time-series forecasting solutions that improved yield, process stability, and operational efficiency.My background also includes:• Enterprise risk & regulatory analytics• Public sector predictive modeling & governance-compliant AI systems• Cloud-native data engineering & large-scale ETL architecture• MLOps, CI/CD automation, and model lifecycle governanceTechnically, I work extensively with Python, SQL, TensorFlow, PyTorch, Vertex AI, Azure ML, BigQuery, Databricks, Redshift, and distributed data pipelines (Beam, Dataflow, Pub/Sub). I’m particularly passionate about Generative AI, LLM orchestration, multi-agent systems, and production-grade AI architecture.Beyond technical delivery, I enjoy mentoring teams, influencing AI strategy, and translating complex machine learning systems into measurable business impact.If you’re working on AI transformation, GenAI systems, or large-scale ML platforms, I’d love to connect.

Experience

1. Senior Data Scientist

   Google

   Nov 2024 — Present · CA, US

   Working on large-scale Generative AI and search systems, leading end-to-end AI/ML initiatives from problem definition and KPI design to production deployment and monitoring. Designing cloud-native AI architectures on GCP using BigQuery, Vertex AI, Dataflow, Pub/Sub, Cloud Run, and GKE. Building Learning-to-Rank models, transformer-based NLP systems (BERT), vector embedding pipelines, and Retrieval-Augmented Generation (RAG) architectures using Gemini to improve search relevance, personalization, and conversational intelligence. Implementing Agentic AI workflows with multi-agent orchestration, tool-augmented LLMs, and autonomous reasoning pipelines. Driving experimentation, A/B testing, MLOps, CI/CD automation, and model governance to deliver scalable, measurable business impact

Education

• Geethanjali College of Engineering and Technology

  Bachelor's degree, Electrical, Electronics and Communications Engineering

• University of Memphis

  Master's degree, Management Information Systems, General