jeneel = {
"role" : "AI/ML & Full-Stack Engineer",
"education" : "M.S. Artificial Intelligence — University of Bridgeport (2026)",
"location" : "United States · Open to Remote",
"available" : True,
"focus" : ["RAG Systems", "LLM Fine-Tuning", "Production ML", "Full-Stack AI Apps"],
"currently" : "Building agentic AI systems with LangGraph, GPT-4o & vector retrieval",
"philosophy" : "Models that ship beat models that benchmark.",
}I architect models and ship the interfaces around them. From fine-tuned LLMs with grounded retrieval to production ML monitoring pipelines — I build AI that works outside the notebook, with reliability humans can trust.
|
Cybersecurity threat intelligence assistant — fine-tuned Llama-3.1-8B on 9,992 NVD CVE records with dual-source RAG grounding (live NVD API + threat actor KB). Zero hallucinations on benchmark. SSE streaming. |
Production-grade ML monitoring system for credit card fraud detection — auto-detects data drift, concept drift & performance degradation, then retrains the model without human intervention. |
AI / ML / LLMs
$ git log --oneline -4
→ Architecting an Agentic AI Research Assistant (LangGraph + GPT-4o + RAGAS)
→ Finishing M.S. thesis: DocGuard AI — privacy-aware RAG with hallucination guard
→ Deepening MLOps: drift detection, auto-retraining, evaluation pipelines
→ Open to AI/ML Engineer & Software Engineer roles — May 2026 onward
