AI / ML Engineer Intern
LivePerson Inc.New York, NY
Built prompt optimization systems to enable quick and efficient migration to different LLMs and LLM providers.
Vijay Ram Enaganti
I specialize in Generative AI and Machine Learning.
I build AI products at the intersection of research, systems, and product.
Exploring new avenues and opportunities to build intelligent systems that solve real-world problems.
Favourite line: "Humans are smart enough to invent AI, dumb enough to need it, and so stupid that we can't figure out if we did the right thing." - Jerry Seinfeld
Information and Reach
- GitHub
- Blogs on Hashnode
- San Francisco Bay Area, California
Role
Applied AI / ML Engineer
Focus
- Modern AI Research and Engineering
- Generative AI
- Prompt Engineering
- Machine Learning
- Data Science
- AI Product Development
Experience
Machine Learning Research Intern
Center for Information Security, Forensics and Cyber Security Research (C-ISFCR) @ PES UniversityBangalore, India
Real-time video analysis for anomaly detection using deep learning models.
Projects
Duration
·7 DAYS
Activity
25
Project Hawkeye - Autonomous QA Testing Agent
AI AGENT - QA AUTOMATION
An autonomous QA testing system that uses LLM-driven agents to execute browser-based test plans. Features a Think→Act→Decide cycle for intelligent navigation and verification, running in isolated Docker sandboxes for maximum reliability.
LangGraphFastAPIReactPlaywrightnoVNCDocker
Duration
·33 DAYS
Activity
18
Project Sensei - Privacy-First Local AI Agent
AI AGENT - LOCAL - PRIVACY
A privacy-first local AI agent that runs entirely on your machine. Built with LangChain, LangGraph, Ollama, FastAPI, and React. Sensei can search your files, read documents (PDF, DOCX, code, configs, images), analyze logs, explore directory structures, run semantic search, inspect git changes, and more — all without sending data to the cloud.
LangChainLangGraphOllamaFastAPIReactViteSQLite
Education
M.S. Computer Science
University of California, RiversideRiverside, CA
Specialized in Artificial Intelligence and Systems Architecture.
B.S. Computer Science and Engineering
PES UniversityBangalore, India
Python programming and core computer science fundamentals.
Writing & Notes
Blog
My implementation of TurboQuant algorithm by Google
I implemented the TurboQuant algorithm by Google in PyTorch.
ResearchAIPyTorchOptimizationLLMK-V CacheQuantizationGoogle
Read on Hashnode →