Software Developer Engineer

Veeresh Koliwad

602-***-**** ****************@*****.*** linkedin.com/in/veereshkoliwad github.com/veereshgit99 Summary

Software Engineer with 2.5+ years of experience building distributed backend systems and deploying scalable cloud solutions. Led ML-driven automation, improved API performance by 30%, and built microservices that cut order processing time by 90%. Passionate about system design, performance tuning, and real-world ML applications. Education

Arizona State University Tempe, AZ

Master’s in Computer Science Jan. 2024 – Dec. 2025 RV College of Engineering Bangalore, India

Bachelor’s in Computer Science Aug. 2017 – May 2021 Experience

Associate Software Developer Jul. 2021 – Dec. 2023 SAP LABS Bangalore, India

• Built a purchase order microservice for SAP ERP to automate manual workflows, reducing processing time by 90% for 5K+ monthly orders.

• Migrated legacy applications to SAP Cloud, cutting infrastructure costs by 20% and improving scalability.

• Optimized API response time by 30% using Redis caching, improving overall user engagement by 20%.

• Led development of a bug prediction tool with a 4-member team, reducing support tickets by 25%. Research Assistant Jan. 2025 – Present

Arizona State University Tempe, AZ

• Evaluated MiniLLM on benchmark datasets (OpenOrca, AlpacaEval) to explore trade-offs in LLM compression through knowledge distillation .

• Reduced inference latency by 45% using LayerDrop and pruning techniques, making compressed LLMs more practical for deployment.

Software Development Intern Feb. 2021 – Jul. 2021

SAP LABS Bangalore, India

• Developed a Jira workflow gadget using JavaScript and HTML, used by 10+ teams to simplify ticket tracking.

• Built and deployed full-stack features using React and MongoDB on AWS, for SAP’s Bydesign module. Projects

Football Analysis System Python, YOLOv8, OpenCV, KMeans, Optical Flow Jun. 2024 – Aug. 2024

• Built a real-time player/ball detection system using YOLOv8, achieving 95% accuracy on Bundesliga datasets.

• Implemented KMeans clustering for team identification and optical flow for tracking player movements.

• Applied perspective transformation to standardize camera angles across match footage. RAG Chatbot LangChain, Hugging Face, ChromaDB, Vector Search Jan. 2025

• Developed a context-aware chatbot using Retrieval-Augmented Generation (RAG) to integrate real-time data with LLMs.

• Optimized response accuracy by implementing vector search and data chunking in ChromaDB.

• Deployed the system with Flask API for seamless integration with frontend applications. Technical Skills

Languages: Python, C/C++, Java (Intermediate), SQL, JavaScript, HTML/CSS Machine Learning: NLP, Computer Vision, LLMs, Recommendation Systems Tools: Docker, Kubernetes, React, Kafka, Elastic Search, Redis, Git Cloud & Databases: AWS, SAP Cloud Platform, PostgreSQL, MongoDB Methodologies: REST APIs, Microservices, Distributed Systems, Agile, CI/CD

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