@skantar1
About
Senior ML Engineer | GenAI + RAG Systems | Fine-tuning | MLOps | Conversational & Document AI
Building reliable, real-time AI systems across high-impact domains — from Conversational AI and Document Intelligence to Healthcare, Retail, and Compliance.
At 7-Eleven, I lead GenAI initiatives involving LLM fine-tuning (Mistral, QLoRA, Unsloth), hybrid RAG pipelines, and multimodal agent-based bots.
Domains I specialize in:
Conversational AI (Teams + Claude bots, product QA agents)
Document AI (OCR + RAG, contract Q&A, layout parsing)
Retail & CPG (vendor mapping, shelf audits, promotion lift)
Healthcare AI (clinical retrieval, Mayo Clinic work)
MLOps & Infra (Databricks, MLflow, vector DBs, CI/CD)
Multimodal Vision+LLM (part lookup from images)
I work at the intersection of LLM performance, retrieval relevance, and scalable deployment — making AI not just smart, but production-ready.
Let’s connect if you’re exploring RAG architectures, chatbot infra, or fine-tuning strategy!
Available for
I'm available for: Tech talks & guest blogs on RAG, LLM fine-tuning, and GenAI infra Collaboration on open-source or academic AI/ML projects (LLMs, agents, retrieval) Advisory roles for startups exploring AI system design or MLOps strategy Freelance/consulting in Conversational AI, Document AI, or GenAI infra Mentorship for engineers transitioning into GenAI/ML from traditional data roles
Sai Sandeep Kantareddy's blogs
Recently published
Beyond Bigger Models: Building Intelligent Multi-Model AI Systems
Mar 24 · 5 min read · Introduction Over the past few months, the narrative around AI has been dominated by one idea: Bigger models → better intelligence. But after experimenting with: local models (Qwen via Ollama) codin
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Building a Conversational Shopping Search System That Truly Understands User Intent (Part 2)
Mar 16 · 10 min read · Beyond Embeddings: The Agent-Based Architecture Revolution In Part 1, I explored how embedding-driven search can understand user intent far better than traditional keyword matching. But understanding
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AI Is an Engineering Problem Again
Feb 9 · 6 min read · How to Choose Careers and Build Teams in the Agent Era 1. Why this document exists The AI ecosystem today is loud, fragmented, and confusing. Students don’t know what to study Engineers don’t know how to stay relevant ML graduates don’t know where...
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