warming /agents /rag /mlops
Building scalable, production-ready AI and software systems across Computer Vision, NLP, and Agentic AI.
7+ years • Senior ML Engineer & SWE — production deployments, agentic orchestration, and CI/CD at scale.
Senior Machine Learning Engineer and Software Engineer with over 6 years delivering enterprise-grade AI and software solutions. I focus on moving models into production — writing reliable model code, robust APIs, and repeatable deployment pipelines.
My work spans Computer Vision, NLP, and agentic systems that automate analytics and workflows. I prefer shipping maintainable code and building observability into ML systems from day one.
I enjoy open-source tooling and pragmatic engineering: making complex systems simple to operate and measure.
Led engineering for Fractal AI (India's First AI Unicorn Company), a multi-agent orchestration platform (LangGraph / LangChain). Owned tool onboarding and metadata lifecycle to productize agent behaviors for largest US telecom's business use.
Implemented human-in-the-loop feedback and automated deployment flows; added Label Studio + FastAPI annotation pipelines, Trivy scanning, MLflow tracking and Seldon serving.
Built a real-time liveliness detection service (MTCNN + FaceNet), converted prototypes to modular MLOps pipelines, and established monitoring + retraining flows on AWS.
Delivered AI + ETL systems for smart-factory operations; shipped a 24/7 IPQC audit system (≈200 hours/week saved) and dashboards across 20+ vendor sites.
Completed internships at Tata Consultancy Services and Infosys, gaining hands-on experience in machine learning, data analysis, and software development practices.
Image classification deployed as a Telegram bot. Integrated Weights & Biases for experiment & artifact tracking and a simple MLOps workflow for continuous improvements.
High-accuracy ALPR system with end-to-end pipeline and a Streamlit web app for demo and deployment.
Anti-spoofing pipeline (MTCNN + FaceNet) optimized for low-latency deployment on AWS with pruning/quantization applied.
Real-time deep learning classifier for X-ray images, with notebooks and deployment tooling for evaluation and demo.
Autonomous data-analysis agents that automate EDA, visualization, and report generation — implemented as a folder inside Data-Science-Projects.
Extracts text from PDFs and converts to podcast-style audio using TTS + summarization, with demo scripts and deployment notes inside the parent repo.
Collection of notebooks and demos covering model prototyping, data pipelines, visualizations and small utilities.
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I am eager to join your team and contribute my expertise in Agentic GenAI, software engineering and production-grade ML delivery.
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