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Davit Javadian

@davitjavadian

I build production AI platforms, RAG systems, and machine learning products for healthcare and mobility.

United States
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What I'm looking for

I'm looking to build production AI products that combine LLM applications, machine learning, scalable data systems, and cloud infrastructure to solve real-world business challenges.

At Reapplix, I lead delivery of cloud-native clinical AI platforms that combine EHR, claims, lab, and clinical data for risk analysis and care workflows. I built evidence-grounded RAG and agentic workflows that improved clinical-review efficiency by roughly 30–35%.

Previously at Ford Motor Company, I developed production ML systems for EV fault prediction, vehicle diagnostics, and edge computer vision. My FastAPI diagnostic services supported 10K+ daily requests, while optimized YOLOv7 inference was deployed across 500+ edge devices.

I also built real-time ML, MLOps, and PySpark data platforms at Cognizant, translating business requirements into dependable production solutions. I work across Python, AWS, distributed data systems, LLM applications, and modern software engineering.

Experience

Work history, roles, and key accomplishments

RE
Current

Senior AI Engineer

Reapplix

Dec 2024 - Present (1 year 9 months)

Led a 2-person team in delivering cloud-native clinical AI platforms on AWS, integrating EHR, claims, labs, and clinical data for risk analysis and care workflows. Developed an evidence-grounded retrieval system using RAG with LangChain, embeddings, and pgvector, and orchestrated agentic workflows with LangGraph.

Education

Degrees, certifications, and relevant coursework

University of Southern California logoUC

University of Southern California

Master of Science, Computer Science

2017 - 2020

Pursued a Master of Science in Computer Science at the University of Southern California from 2017 to 2020.

University of California, Berkeley logoUB

University of California, Berkeley

Bachelor of Science, Computer Science

2014 - 2016

Completed a Bachelor of Science in Computer Science at the University of California, Berkeley from 2014 to 2016.

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