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Pandari G
Mid-level Machine Learning Engineer specializing in Generative AI and RAG systems
SephoraSaint Mary's College of CaliforniaSan Francisco, USA5 Years ExperienceMid LevelWorks On-Site
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About
GenAI/LLM engineer with production deployments in both fintech and retail: built an AI-powered mortgage document analysis/automated underwriting pipeline at Fannie Mae (OCR + custom LLM) cutting underwriting review from 3–4 hours to under an hour with privacy-by-design controls. Also helped build Sephora’s GenAI product advisory bot using LangChain-orchestrated RAG (Azure GPT-4, Azure AI Search, MySQL HeatWave vector search), focusing on grounding, evaluation, and compliance-aware architecture choices.
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Built and deployed an AI-powered mortgage document analysis/automated underwriting system reducing review time from 3–4 hours to under 1 hour
Production-grade security for sensitive financial/PII data (anonymization, private VPC subnets, data minimization)
Strong orchestration experience across data/ML/LLM stacks (Airflow, LangChain, Argo CD)
Designed RAG-based conversational product advisor with grounded recommendations (Azure ChatGPT + Azure AI Search + MySQL HeatWave vector search)
Systematic evaluation approach for LLM workflows using KPIs, automated tests, RAGAS/LangChain eval, and human-in-the-loop feedback
Improved classification of ambiguous financial transactions via semantic grounding with retrieved labeled examples injected into prompts
Pragmatic architecture decisions balancing latency, compliance, and operational overhead (chose MySQL HeatWave over Pinecone to meet InfoSec constraints)
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Experience
ML/AI EngineerSephora · Jan 2024 – Present
Data Scientist with MLFannie Mae · Jun 2021 – Aug 2023
Python DeveloperCRISIL · Jul 2020 – Mar 2021
Education
Saint Mary's College of Californiamaster, Business Analytics
Birla Institute of Technologymaster, Math and Computing
Intern Machine Learning Engineer specializing in LLM agents and multimodal reasoning
Mountain View, CA2y exp
Corvic AICarnegie Mellon University
“LLM/agent engineer who built a production code-generation agent at Corvic AI that lets non-technical users query CSV/tabular data in natural language by generating and executing Python. Focused on making LLM systems reliable and scalable via schema-aware validation, sandboxed execution-feedback retries, prompt caching/embeddings, async execution, and high-throughput data processing with Polars; also partnered with Adobe product/marketing to ship brand-aligned AI content generation for email and push notifications.”