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Building intelligent systems at the intersection of AI, backend engineering, and real-world impact.
class NithishKumar: name = "Nithish Kumar" role = "AI Engineer" stack = [ "Python", "FastAPI", "Flask", "ML" ] goals = [ "Build AGI-era products", "Scale AI systems", "Impact millions" ] status = "Open to work 🚀" def __init__(self): self.exploring = [ "RAG pipelines", "MCP agents" ]
I'm Nithish Kumar, a Computer Science student on a focused path toward becoming an AI/ML Engineer. I build systems that sit at the crossroads of intelligent automation and practical software — things that solve real problems, not just demo well.
My work spans backend APIs, machine learning pipelines, and multi-agent AI systems. I think deeply about architecture, care obsessively about reliability, and ship with the confidence of someone who has won a hackathon with a production-grade system under pressure.
Right now, I'm pushing toward roles where I can scale AI systems that create genuine impact — in legal tech, productivity, or anywhere intelligence can replace friction.
EPOCHON · 2025
Built a multi-agent Smart Legal AI system from scratch during the hackathon — featuring a Self-Doubt Engine for safety-first AI decisions, a Smart Scribe petition generator, compliance monitoring, and automated hearing scheduling. Judges awarded First Prize for production-grade architecture and real-world applicability.
First Prize
Epochon 2025
AI & ML workshop completion at one of India's most prestigious technical festivals — deepened practical knowledge in modern ML techniques and hands-on engineering.
Contributed to open-source projects within the amFOSS developer community — collaborated on real codebases and sharpened collaborative engineering practices at scale.
AI systems, backend APIs, and developer tooling — engineered for real-world impact.
An intelligent, safety-first legal assistant with 7 specialized agents — Research, Document Analysis, Procedure Guidance, Compliance Monitoring, Smart Scribe, Self-Doubt Engine, and Hearing Scheduler. Built and won First Prize at Epochon Hackathon.
Smart kitchen inventory & grocery planning system. Tracks ingredients, estimates consumption via behavior-based learning, generates predictive grocery recommendations, and supports shared household access.
Distill any GitHub repo into an AI-ready ZIP + PDF summary. Handles repos of any size — strips datasets, removes DB binaries, exports schemas, and generates a Claude-powered structured project analysis.
Modular, database-driven personal finance tracker. Secure session-based auth, income/expense management, monthly summaries, and Flask Blueprint architecture. Render-deployment ready.
Open to AI/ML engineering roles, internships, and exciting collaborations. I respond fast.