Kumar Vinay

About Kumar Vinay

I’m an AI/ML Engineer with 5+ years of experience building and deploying production-grade Machine Learning, NLP, and Generative AI solutions across finance and healthcare domains. My work focuses on translating complex business problems into scalable, reliable, and enterprise-ready AI systems that deliver measurable impact.I specialize in Generative AI and Large Language Models, with hands-on experience designing Retrieval-Augmented Generation (RAG) pipelines, agentic AI workflows, and LLM orchestration using LangChain and LangGraph-style architectures. I’ve built systems that combine OpenAI and open-source models with vector databases like FAISS to enable accurate summarization, semantic search, and decision support, while actively evaluating grounding, hallucination risk, and model performance.From an engineering perspective, I bring strong experience in Machine Learning Engineering and data engineering developing end-to-end pipelines covering data ingestion, feature engineering, model training, fine-tuning (LoRA/PEFT), deployment, and monitoring. I’ve deployed cloud-native AI services using Python, FastAPI, Docker, Kubernetes, and MLflow across AWS, Azure, Databricks, and hybrid environments, with a focus on scalability, performance optimization, and operational reliability.I’ve worked closely with global, cross-functional teams spanning data science, engineering, cloud/DevOps, compliance, and business stakeholders. I value ownership, clear communication, and building AI solutions that are not only innovative, but also trustworthy, compliant, and ready for real-world enterprise use.I’m always interested in roles where AI, GenAI, and data engineering come together to drive meaningful transformation.

Experience

1. Ai Ml Engineer

   SMBC Group

   Dec 2024 — Present · NJ, US

   Generative AI (GenAI), Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI, LangChain, LangGraph, Prompt Engineering, Embeddings, Semantic Search, OpenAI APIs, Hugging Face Transformers, LoRA / PEFT Fine-Tuning, Model Evaluation & Optimization, Machine Learning Engineering (MLE), Time Series Forecasting (ARIMA, Prophet, LSTM), XGBoost, Random Forest, FastAPI, REST APIs, AWS (EC2, Lambda, S3, SageMaker), Docker, Kubernetes, MLflow (MLOps / LLMOps), Model Monitoring, Drift Detection, Apache Spark, FAISS, Responsible AI, Enterprise AI Architecture, Global Delivery Collaboration

Education

• Auburn University at Montgomery

  Master of Science - MS, Computer Science