Nagendra Varaprasad

About Nagendra Varaprasad

I build recommendation and ranking systems that move product metrics at consumer scale…

Experience

1. Ai Ml Engineer

   NVIDIA

   Nov 2024 — Present

   Designed and deployed end-to-end machine learning pipelines using supervised and unsupervised learningtechniques (regression, classification, clustering).• Performed feature engineering, data preprocessing, and model evaluation to improve accuracy, stability, andgeneralization in production systems.• Deployed ML models as scalable REST/gRPC inference services, balancing latency, throughput, and cost constraints.• Implemented model monitoring, data quality checks, and drift detection to ensure reliable production performance.• Supported experiment tracking, model versioning, retraining workflows, and A/B testing for reproducible and datadriven deployment decisions.• Participated in ML system design discussions, evaluating batch vs real-time inference and cost–performancetradeoffs.• Worked with deep learning models and optimization techniques for large-scale, performance-critical workloads.• Integrated pretrained large language models (LLMs) into production workflows using prompt engineering andembedding-based representations.• Built and maintained retrieval-augmented generation (RAG) pipelines leveraging vector embeddings and retrievalworkflows.• Contributed to GenAI-powered applications such as AI assistants, search, and summarization features.• Optimized GPU/CPU resource utilization to support high-throughput, low-latency inference in cloud-basedenvironments.• Collaborated cross-functionally with product, engineering, and data teams to deliver measurable business impact.• Applied responsible AI practices, including bias awareness, explainability considerations, and hallucinationreduction strategies