Anish More Email & Phone Number

San Francisco, CA, US

• Implemented a LLM-based system that adapts to user feedback, ensuring generated reports align with the user's unique style. Migrated the system from monolithic to microservices architecture using ECS, reducing system.
• Developed an engaging frontend, increasing user interaction by 35%, and optimized an ETL pipeline, improving data transfer efficiency by 80% and enabling data analysis for the sales team using Supabase and Metabase
• Designed a rag based pipeline that generates personalized, demographically tailored medical reports, enhancing report accuracy and relevance based on patient history and contributing to a $1M ARR milestone
• Created a company-wide protocol leveraging prompt engineering and function calling with LLM APIs, streamlining and democratizing the testing process by enabling non-engineers to actively participate, boosting.
• Architected a modular backend structure to support high traffic loads, leveraging microservices to allow independent scalability, cutting infrastructure costs by 25%.

United States

• Engineered and fine-tuned LLMs such as phi-3, openELM, and Llama3 using torch and transformers, implementing QLoRA and DPO (Direct Preference Optimization) techniques to significantly enhance the quality and automation.
• Deployed a REST API-based medical report automation on Azure, optimizing API endpoints to improve processing efficiency by 15%. Utilized caching and load-balancing for high traffic, ensuring scalable and fault-tolerant.
• Developed a change-tracking tool in Python using difflib and fuzzywuzzy libraries, wrapped in a FastAPI framework for API-driven interactions. This tool implemented customized data structures for tracking and comparing.
• Engineered a REST API for medical term translations using MySQL and SQLAlchemy ORM, employing indexing and optimized query patterns to reduce response times by 30%. Ensured robust data integrity and fault tolerance to.
• Utilized Azure Functions, Blob Storage, and Cognitive Services to create a scalable, efficient workflow pipeline, significantly improving data processing throughput and reducing operational costs by 20%
• Automated infrastructure deployment using Terraform for a consistent, reproducible architecture on Azure, focusing on scalability, fault tolerance, and maintaining low-latency responses

Tennessee, United States

• Architected an LMS similar to Canvas, featuring a discussion board inspired by Stack Overflow. Applied object-oriented principles to boost modularity, and user engagement rose by 45% due to a well-structured user.
• Built a robust REST API using Flask and MySQL for LMS features, including complex notification services with optimized message-passing algorithms to support large-scale push notifications. Ensured data consistency and.
• Integrated JSON for seamless data exchange and leveraged Socket.io for real-time, low-latency communication, ensuring responsive user feedback and robust system interaction under high-load conditions.

Master Of Science - Ms, Computer Engineering

Awards: Second Prize in 2023 UCR Programming Contest (UCRPC) Courses: GPU Architecture, Cloud Computing, Big Data Management, Deep.

Bachelor Of Engineering - Be, Computer Science