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Prakash Chaudhary

Machine Learning Engineer @Fetch

San Francisco, CA, US
MOBILE NUMBERS
+91 *********19

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WORK HISTORY

May 2024 — Present

Machine Learning Engineer @Fetch

Seattle, WA, US

Built and shipped AI Shopping Assistant serving a 200K-user experiment – a Python/LangGraph agent with product card integration (catalog search, web search, 4.2M normalized images at 18x cost efficiency), episode-based conversation history (DynamoDB + S3), and production observability (Opik, OpenTelemetry, Grafana), deployed on AWS ECS Fargate- Built end-to-end LLM evaluation system – a continuous improvement loop connecting offline evaluation (golden dataset), online monitoring (production traces), and human annotation (judge calibration), with CI/CD deploy gating that blocks releases on quality regression- Led Multi-Agent Matching Framework: cross-functional team of 4 engineers; improved match rates by 3.1-3.3 percentage points (73.8%→76.9%) unlocking $165M in GMV; achieved 15% full automation with LLM-as-a-Judge guardrails at 97% accuracy, automating 50+ hours of manual operations to 2 minutes- Developed 3-agent annotation workflow using LangGraph with LLM annotation at 80%+ accuracy to reduce double-annotation to single annotator, cutting total annotation workload by 40% while maintaining dataset quality through human tie-breaking on disagreements- Fully automated RAG pipeline to flag incorrect product matches at 95% recall, protecting ~$800K in GMV annually; replaced manual workflow, reducing daily effort from 8 hours to 15 minutes and saving 40 hours weekly

EDUCATION

2012 — 2014

V.S. Niketan Higher Secondary School

+2, Science

N/A

MITx Courses

Micromasters, Statistics and Data Science

2018 — 2018

NAAMII

Crash Course in AI, Artificial Intelligence

2015 — 2020

Tribhuvan University, IOE, Pulchowk Campus

Bachelor of Engineering (B.E.), Electronics and Communications

N/A

The University of Alabama in Huntsville

Master of Science - MS, Computer Science

ABOUT PRAKASH CHAUDHARY

Machine Learning Engineer with over 5 years of experience designing and deploying scalable end-to-end ML models, with expertise in building AI agents leveraging human-in-the-loop automation to drive measurable business impact.

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