Aug 2024 – Nov 2025 · 1 yr 3 mos · Portland, OR · Remote

• Spearheaded AI & Unified Data team of four engineers to architect scalable Spark data pipelines (300GB+ monthly) and optimize DBT models. Slashed query times from 45s to <10s and enabled real-time analytics for 5K+ users
• Engineered Livmor, a healthcare AI Copilot powered by LLMs and RAG with Datastax Astra. Enabled natural language querying across 50M+ patient records with 93% precision, reducing data access time by 85% for 1M+ monthly queries.
• Architected NorEntropy, an unstructured-to-structured data pipeline utilizing custom entity extraction models to process 50B+ tokens quarterly with 95% accuracy, unlocking analytics for a $3M product line.

Jul 2023 – Jun 2024 · 11 mos · India · Remote

• Conducted comprehensive analysis of AI models for Remotasks(ScaleAI), resulting in improved accuracy, performance, and overall project success.
• Utilized advanced data analysis techniques to optimize AI models, leading to increased efficiency and effectiveness of Remotasks(ScaleAI) projects.
• Full-stack development for a prominent grocery delivery service.
• Worked extensively on AWS EC2, S3, Route 53, and Lightsail to ensure seamless scalability and reliability of the platform.
• Configured Elastic Load Balancer and implemented firewall measures to enhance website security and performance.
• Created and maintained complex databases comprising customer profiles, orders, returns, refunds, and loyalty points,
• Engineered SQL-based workflows for automated report generation on critical metrics like Low Inventory, Revenue, Profit-Loss, and Mileage driven per zone, streamlining decision-making processes.
• Designed and optimized data models to support real-time analytics and long-term storage requirements.
• Developed and maintained backend systems, improving overall system efficiency and user experience.

Jan 2023 – Jun 2023 · 5 mos · Bengaluru, Karnataka, India · On-site

• Developed the "Customer Journey" Full-stack web-app, starting from conceptualizing the high-level design (HLD).
• Implemented robust solutions to extract data from diverse sources including Redshift, S3, and DynamoDB, with additional querying in Redshift using Athena, ensuring precise order attribution accuracy in various edge cases.
• Focused on enabling seamless global tracking of order attribution and non-attribution as the primary goal of the project.
• Achieved a substantial decrease in customer queries by nearly 15,000 related to order attribution and non-attribution, showcasing the project's effectiveness.
• Worked closely with the Senior Manager to introduce an automation system for generating monthly "MSR" reports. This innovative approach revolutionized data collection from various Amazon internal services, enhancing operational efficiency and productivity across the board.

May 2022 – Jun 2022 · 1 mo · Gurugram · Remote

Jan 2022 – Apr 2022 · 3 mos · Bhubaneshwar, Odisha, India · Remote

• Created and implemented a robust, end-to-end AI-powered FinTech B2B invoice management solution.
• Incorporated advanced machine learning algorithms to maximize efficiency, precision, and financial decision-making within the application.
• Revolutionized the invoice management process for B2B transactions by automating and streamlining it entirely.
• Significantly improved operational effectiveness and precision in financial management for businesses.

Sep 2021 – May 2022 · 8 mos · Bengaluru, Karnataka, India · Remote

• Developed and fine-tuned deep-learning neural network models:
• The first model focused on enhancing Samsung's flash portrait studio lighting software, contributing to improved picture quality.
• The second model centered on Sky Segmentation, enhancing image & video processing capabilities.
• Leveraged Python and Machine Learning techniques extensively for model development, gaining valuable experience in these technologies.
• Additionally, I undertook the task of developing an Android application to facilitate the front-end implementation of these models, effectively bridging the gap between cutting-edge AI models and user-friendly applications.