class KunalBisht:
role = "AI Engineer"
location = "Pithoragarh, India 🏔️"
currently_working_on = [
"LLM pipelines with real evaluation",
"RAG systems that don't hallucinate",
"NLP — entity detection, intent classification",
"Full-stack AI apps",
]
learning = ["Agentic AI workflows", "Hybrid retrieval", "RAGAS evals"]
open_to = "AI Engineer / GenAI Developer roles"
contact = "kunalbisht909@gmail.com"|
AI Meeting Intelligence Platform Transcript analysis app that takes audio and extracts intents, anonymizes PII, and summarizes — all without letting the LLM see raw sensitive data.
|
Open-Book QA over 241,000 Articles Built a RAG system over a large Wikipedia index to ground LLM answers in actual sources instead of letting it guess.
|
|
ML Transport Delay Predictor End-to-end ML pipeline from raw CSV to a deployed prediction API with dashboards. My first real attempt at the full MLOps cycle.
|
APIs & Microservices Built and maintained backends for a few production platforms. Learned a lot about what breaks at scale.
|
- Getting better at LLM evaluation (DeepEval, RAGAS)
- Exploring hybrid dense/sparse retrieval for RAG
- Learning more about agentic AI and multi-step reasoning
- Contributing to open-source AI tooling
Looking for AI Engineer / GenAI Developer roles. Happy to chat!
