Jan 2025 – Oct 2025 · 9 mos · New York, United States · Hybrid

• Engineered complex BigQuery SQL pipelines with nested CTEs and window functions, extracting insights from 8M+ records to drive executive decision-making and business compliance strategies.
• Automated data movement and validation workflows between BigQuery and AWS S3, improving data quality checks and reducing manual effort by 40%.
• Built dynamic Google Sheets dashboards linked to live SQL sources, enabling real-time reporting and cross-team collaboration for legal and copyright risk monitoring.

Dec 2023 – Dec 2024 · 1 yr · New Jersey, United States · Remote

• Developed pricing and demand forecasting models (PyTorch, TensorFlow) that boosted profit margins by 10% and improved forecast accuracy by 12%, driving data-informed pricing strategies.
• Built and deployed a full-stack, role-based AI ordering platform using React, Node.js, and Supabase, enabling admins, retailers, and customers to manage products, orders, and inventory seamlessly.
• Integrated AI agents powered by Gemini LLM + RAG architecture to automate retailer order placement, handle customer support queries, and dynamically recommend nearby stores — enhancing user engagement and operational efficiency.

May 2023 – Dec 2023 · 7 mos

• Designed and deployed production-ready LLM systems with LangChain + LangGraph, powering context-aware RAG pipelines and multimodal reasoning for enterprise data and customer apps.
• Built full-stack AI platforms using Angular (TypeScript), Node.js + PostgreSQL, and REST APIs, integrating Gemini / OpenAI LLMs and AI agents for intelligent analytics and customer automation.
• Implemented MLOps + DevOps pipelines on Azure with Docker, MLflow, and GitHub Actions, accelerating deployment cycles by 40% and improving model reliability by 25%.

May 2022 – May 2023 · 1 yr · Remote

• Engineered ML-driven recommendation engines and fraud detection models using Python, FastAPI, and Scikit-learn, boosting client operational efficiency by 18% through intelligent automation.
• Designed and implemented scalable data pipelines for ingestion, feature extraction, and real-time inference, enabling consistent performance across large datasets and multiple clients.
• Built and deployed full-stack AI applications using React and Node.js, integrating REST API endpoints for serving models and analytics dashboards across web platforms.
• Orchestrated automated MLOps pipelines (Docker, GitHub Actions, cloud deployment) that reduced release cycles by 30% and improved uptime and monitoring by 20% through proactive reliability enhancements.

Feb 2021 – Apr 2021 · 2 mos · Ahmedabad, Gujarat, India

• Developed machine learning models for movie recommendation, breast cancer classification, and sentiment analysis.
• Applied classification, regression, and clustering techniques for model prototyping.
• Participated in data exploration and processing efforts.

Jan 2021 – Apr 2021 · 3 mos · India

Jul 2020 – Mar 2022 · 1 yr 8 mos

• Led a 10-person team of app developers at Think-Digital, SRM in Chennai, Tamil Nadu, India.
• Improved project scheduling and task delegation to deliver 8 high-quality applications on schedule.
• Facilitated detailed interactions to gather comprehensive requirements and implement feedback.
• Conducted team discussion sessions with over 60 people.
• Organized and conducted hands-on workshops to impart practical knowledge on Node.js, Angular, and JavaScript, successfully training participants on building modern web applications and fostering a deeper understanding of fullstack development.

Aug 2018 – Jul 2020 · 1 yr 11 mos

• Developed hybrid applications using Angular, Ionic, Node.js, and other technologies for campus event management and student networking.
• Utilized MySQL, Firebase, and other platforms to create seamless user experiences for web and mobile applications.

May 2020 – Sep 2020 · 4 mos · Remote