Software Engineer (AI/ML) at The University of Texas at Austin

Developed a large-scale semantic similarity pipeline using LLM embeddings and PyTorch to vectorize and match hundreds of thousands of patent and technology records against funding opportunities (state, federal, VC), improving relevance, precision, and throughput while reducing manual review time. Built a natural language search engine using Python, RAG architecture, and LLM embeddings, processing 1M+ repositories with 50% improved search relevance vs. keyword-based systems. Partnered with product and engineering teams to migrate a legacy Java Spring Boot application to modern Python Django, rewriting business logic, containerizing, and deploying on Docker and Kubernetes—reducing deployment time by 40% and improving system performance by 30%. Created Microsoft Power Automate workflows to automate repetitive business processes, generating reports and newsletters and saving 120+ staff hours monthly while reducing labor costs by 25%.

Software Engineer (AI/ML) at Discovery to Impact - University of Texas at Austin

Lead AI/ML software engineer building large-scale ML pipelines; vectorizing patents and tech records using LLM embeddings to match hundreds of thousands of records against funding opportunities; leveraged dense representations and similarity search to improve relevance, precision, and throughput while reducing manual review time. Built natural language search engine using Python, RAG architecture, and LLM embeddings with GitHub Copilot-assisted development, processing 1M+ repositories. Partnered with product and engineering teams to migrate a legacy Java Spring Boot application to modern Python Django, rewriting business logic, and containerizing with Docker and Kubernetes—reducing deployment time by ~40% and improving system performance by ~30%. Created Microsoft Power Automate workflows to automate repetitive business processes, generating automated reports and newsletters that save 120+ staff hours monthly and reduced labor costs by 25%.

Software Engineer (AI/ML) at Discovery to Impact, University of Texas at Austin

Led development of production AI/ML solutions focused on generative AI, deep learning, and computer vision. Architected end-to-end ML pipelines, deployed GPU-optimized models, and implemented scalable solutions across NLP and multimodal AI. Collaborated with cross-functional teams to translate research into production-ready systems.

Backend Developer at Texkaar Innovations

Developed and deployed 20+ RESTful APIs and microservices using Java, Spring Boot, and Maven, improving system scalability by 30% and reducing operational costs by 25% through performance optimization. Implemented an AI-driven recommendation engine using Python and scikit-learn, applying LLM embeddings to improve content personalization by 20% across 500K+ daily user interactions.

Backend Developer at Texaar Innovations

Developed and deployed 20+ RESTful APIs and microservices using Java, Spring Boot, and Maven, improving system scalability by 30% and reducing operational costs by 25% through performance optimization. Implemented AI-driven recommendation engine using Python and scikit-learn, applying LL M embeddings to improve content personalization by 20% across 500K+ daily interactions.

Backend Developer at TEKSAAR Innovations

Migrated legacy Java Spring Boot applications to modern Python Django, containerized and deployed with Docker and Kubernetes, reducing deployment time by 40% and improving system performance by 30%. Built 20+ RESTful APIs and microservices, and implemented AI-driven recommendations using Python and scikit-learn to improve content personalization.

Webdunia Software Engineer at Webdunia

Designed and implemented a C# .NET application for content management with secure APIs and backend services, reducing query turnaround time by 70% and decreasing analyst workload by 80%. Deployed .NET services on Azure App Service and Azure SQL, implementing security controls and compliance checks that reduced infrastructure costs by 10%. Built an NLP-to-SQL translation system using Python and TensorFlow, automating query generation and achieving an F1 score of 0.94 on production datasets. Developed object detection models for food classification that secured additional AI-driven contracts, demonstrating the ability to translate AI research into business-impacting products.

Web Development / Software Engineer (Web) at Webdunia Software Engineer

Designed and implemented a C# .NET application for content management with secure APIs and backend services to reduce query turnaround time and analyst workload. Deployed .NET services on Azure App Service and Azure SQL, implementing security controls and compliance checks to reduce infrastructure costs. Built an NLP-to-SQL translation system using Python and TensorFlow to automate query generation, achieving an F1 score of 0.94 on production datasets. Developed object detection models for food classification securing additional AI-driven contracts. Built Python-based deep learning pipelines for multimodal systems including a production-ready pneumonia classification approach and other applied AI projects.

Web Software Engineer at Webdunia Software Engineer

Designed and implemented a C# .NET application for content management, building secure APIs and backend services that reduced query turnaround time by 70% and decreased analyst workload by 80%. Deployed .NET services on Azure App Service and Azure SQL, implementing security controls and compliance checks to reduce infrastructure costs by 10%. Built an NLP-to-SQL translation system using Python and TensorFlow to automate query generation, achieving an F1 score of 0.94 on production datasets. Developed object detection models for food classification securing additional AI-driven contracts; demonstrated ability to translate AI research into business-impacting products.