Phanindra Maddipatla

Maddipatla Phanindra-- linkedin.com/in/mphani/ github.com/phani06041 Bengaluru,Karnataka Profile Motivated Software Engineer currently working as an Associate Data Analyst at Sagility. Passionate about delivering state-of-the-art software solutions and leveraging data to drive informed decision-making. Proficient with Python and its data analysis frameworks, as well as SQL. Professional Experience AI/LLM Training Specialist TURING Worked as part of Turing’s AGI initiative, contributing to the training and fine-tuning of Large Language Models (LLMs) for enterprise-grade solutions. Delivered high-quality language data, feedback, and testing protocols aligned with client-specific goals. 2024 Sep – present Associate Data Analyst SAGILITY 2024 Jun – 2024 Dec Bengaluru, India Teaching Assistant - Cloud Computing PES University 2024 Jan – 2024 May Teaching Assistant - DBMS PES University 2023 Aug – 2023 Dec Teaching Assistant - OOADJ PES University 2024 Jan – 2024 May Coding Ninjas Campus Ambassador My role was to promote the test series and various Hackathons conducted by coding ninjas.My role also includes promoting the Coding Ninjas platform and referring as many students as possible.I have received many vouchers and coupons for my performance 2022 Jun – 2023 May Skills Mysql Python Computer Networks C Operating systems Education Bachelor of Technology - Computer Science and Engineering PES University CGPA:8.14 Awarded the DAC scholarship for Excellence in Academics for the 1st, 2nd and 3 rd year 2020 – 2024 Bengaluru, India • 12th Grade NARAYANA JR COLLEGE Percentage: 96.7% 2018 – 2020 10th Grade NARAYANA EM HIGH SCHOOL Percentage: 98% 2017 – 2018 Maddipatla Phanindra - Projects AI/LLM Training Specialist TURING (Clients: Microsoft, Meta) 2024 Sep – present Overview: Worked as part of Turing’s AGI initiative, contributing to the training and fine-tuning of Large Language Models (LLMs) for enterprise-grade solutions. Delivered high-quality language data, feedback, and testing protocols aligned with client-specific goals. Key Contributions: Client: Microsoft Collaborated on refining LLM responses for enterprise use cases. Provided human-in-the-loop (HITL) feedback for prompt/response optimization. Helped align model behavior with Microsoft’s Responsible AI principles. Participated in evaluation cycles for improving contextual relevance and coherence. • • • • • Client: Meta Worked on training datasets focused on conversational quality and factual grounding. Engaged in reinforcement learning from human feedback (RLHF) workflows. Evaluated model hallucination tendencies and recommended improvements. Assisted in benchmarking output against open-source LLMs for comparative analysis. • • • • • Tools & Skills: Prompt engineering, LLM evaluation, RLHF, data annotation, Python (for internal tools), AI safety practices. Resolution Scanning System HUMANA Leading the development of an advanced medical document processing system designed to extract critical information from healthcare documents. The system employs machine learning algorithms to classify documents as expedited or non-expedited, while simultaneously determining request types (PRE or POST authorization). Key Responsibilities: Engineered a robust classification model for accurate medical document categorization Implemented comprehensive confidence scoring mechanisms for extracted field data Currently optimizing the confidence calculation algorithms to improve system reliability Developed a hierarchical accuracy assessment framework that prioritizes critical fields Created document-level precision metrics to evaluate overall system performance Technical Achievements: Enhanced model accuracy through iterative rule refinement and parameter optimization Established quality control protocols for continuous system improvement Designed performance analytics dashboards to track key accuracy metrics Implemented confidence thresholds to flag potential misclassifications for manual review This project streamlines HUMANA's document processing workflow, reducing manual review time while maintaining high accuracy standards for critical healthcare determinations. 2024 Aug – present • • • • • • • • • Discriminatory Speech Detection Using NLP and ML techniques This Project involves a model built with deep neural networks and NLP techniques to detect discriminatory speech in text The model will be optimised with a Bio-inspired meta-heuristic algorithm to further classify the given text into multiple classes like misogyny, religion, race, and disability 2023 – 2024 • • AI LEARNS TO PLAY FLAPPY BIRD (PYTHON) Python , NEAT and ANN algorithms Our Project simulates the basic understanding of the Genetic Algorithm. Where the birds are populated based on certain inputs, the AI understands how to play the game • Maddipatla Phanindra - Criminal Record Management System The project is a web-based application and has CRUD (Create, Read, Update, and Delete) Operation functionalities. Movie Recommendation system Python Designed and implemented a movie recommender system with model-based collaborative filtering, yielding an RMSE of 0.2125 for accurate user-based movie recommendations. Nashville Meetup Analysis Conducted in-depth Social Network Analysis (SNA) of the Nashville Meetup community, identifying top influencers and interest group dynamics. Project Management System Python,Mysql This project is a PHP framework which is used to manage and handle the multiple users' projects easily without any hassle. Text based Adventure Game Python This is a simple game that is built using python.Built some mini-games and also some of the textual questions that will be displayed in some of the tiles when we enter. Certificates Introduction to Data Science & AIML Machine learning with python Mastering Data structures and Algorithms using C and C++ Introduction to Cloud 101 - AWS Educate (EC2, RDS, VPC, IAM) Languages English | Hindi | Telugu Maddipatla Phanindra -