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Keerthi kolan - Data Engineer/AI/ML

[email protected]

Location: Kyle, Texas, USA

Relocation: yes

Visa: OPT

Resume file: keerthi_kolan_resume_1775666589222.pdf Please check the file(s) for viruses. Files are checked manually and then made available for download.

PROFESSIONAL SUMMARY M.S. Computer Science graduate with experience in building scalable backend services, cloud-native applications, and client facing solutions. Skilled in Java, Python, C#, JavaScript/TypeScript, SQL, and modern frameworks, with expertise in Microsoft Azure and automated data pipelines. Strong foundation in AI/ML and Large Language Models (LLMs), including ChatGPT-style assistants and retrieval-augmented pipelines. EXPERIENCE Machine Learning Research Intern | RooGenAI July 2025 Present Pioneered the first neural network on an ultra-low-power AI accelerator, demonstrating greater than 95% accuracy in image classification Developed a custom ML runtime in Python/NumPy, implementing core algorithms (e.g., Conv2D, backpropagation) from scratch to enable validation of 50+ model architectures incompatible with PyTorch/TensorFlow Prototyped a Retrieval-Augmented Generation (RAG) pipeline using LangChain and OpenAI GPT models, enabling domain-specific document Q&A with improved accuracy and reduced hallucinations Software Engineer | Chronodat July 2021 July 2023 Contributed to the development of a licensing microservice using C# and Azure Functions, scaling from prototype to pro duction to support 10K+ daily license validations Automated payroll and onboarding data pipelines with SQL, Azure Functions, and Power Automate, saving 15+ hours weekly for 50+ client organizations (20K+ employees) and improving partner satisfaction Built and standardized front-end modules using React, TypeScript, JavaScript, HTML, and CSS, ensuring seamless HTTP-based integrations, eliminating UI inconsistencies, and reducing feature development time by 25% Migrated applications to Azure (App Service, Functions, SQL Database, Blob Storage, Key Vault, Service Bus), improving resource efficiency and reducing cloud expenses by over 20% Orchestrated CI/CD pipelines with GitHub Actions, Docker, and Terraform, shrinking release cycles from 14 days to 3 days Software Engineer Intern | Chronodat April 2021 June 2021 Implemented RESTful APIs in Java Spring Boot for core application features including an Application Tracking System and Time-Off Reporting System, enabling seamless data exchange and reducing manual HR processing time Built reusable React components for internal dashboards, streamlining state management and reducing front-end implemen tation time for new features by approximately 20% EDUCATION California State University, East Bay, CA August 2023 May 2025 Master of Science in Computer Science Coursework: Web Systems, Advanced Algorithms, Cloud Computing, Machine Learning Jawaharlal Nehru Technological University, Hyderabad, India Bachelor of Technology in Computer Science and Engineering GPA: 3.97/4.00 August 2019 July 2023 GPA: 8.37/10.00 Coursework: Object-Oriented Programming, Data Structures, DBMS, Distributed Systems TECHNICAL SKILLS Core Languages: Java, Python, C++, C#, JavaScript, TypeScript, SQL Frameworks: React, Node.js, Express, Django, Redux, Spring Boot Systems & Databases: PostgreSQL, MySQL, MongoDB, DynamoDB, NoSQL Cloud & DevOps: Microsoft Azure (App Service, Functions, SQL Database, Blob Storage, Key Vault, Service Bus, DevOps), AWS (EC2, S3, Lambda), Docker, Kubernetes, CI/CD, Terraform AI/ML & LLMs: Hugging Face Transformers, LangChain, OpenAI APIs, Scikit-learn, PyTorch, TensorFlow Data Pipelines: SQL, ETL, Pandas, Azure Data workflows, AWS Transcribe, REST/GraphQL APIs Additional Tools: Git, GitHub, GraphQL, Postman, Visual Studio, Figma PROJECTS Context-Aware Chatbot with Secure Full-Stack Pipeline [GitHub] Built a ChatGPT-style interface using the MERN stack to enable real-time messaging with persistent chat history Integrated OpenAI s GPT API into backend services to deliver context-aware conversational responses Implemented authentication using JWT, HTTP-only cookies, and password encryption to ensure secure user data management Scalable Media Transcription System (AWS Serverless) [GitHub] Architected a serverless pipeline on AWS (S3, Lambda, API Gateway, Transcribe) to automate audio transcription, designed for zero operational overhead and automatic scaling Engineered a React frontend that reduced a previously 15-minute manual upload process to a single click, providing real-time status tracking and improving user productivity Keywords: cplusplus csharp continuous integration continuous deployment artificial intelligence machine learning user interface javascript sthree California