I am a machine learning engineer focused on building scalable data platforms in healthcare. I architected an enterprise health care data normalization platform using LangChain and OpenAI embeddings, processing 2M+ GHX records per month with 95% entity-resolution accuracy and reducing downstream defects by 80% while removing 160+ manual hours per month. I also developed autonomous GPT agent workflows to orchestrate Selenium and PyAutoGUI across GHX, Lawson, and SAP, cutting analyst data-entry time by 75% and eliminating 90% of human errors. I currently lead a team of engineers to deploy AI-driven pipelines, including RAG cleaning and data-migration workflows, exposing LLM-callable Python modules across multiple portals with robust cross-system accuracy. My work improves governance, SLA performance, and operational resilience across hospital networks while driving cost savings and scalable delivery.

Saloni Patadia

I am a machine learning engineer focused on building scalable data platforms in healthcare. I architected an enterprise health care data normalization platform using LangChain and OpenAI embeddings, processing 2M+ GHX records per month with 95% entity-resolution accuracy and reducing downstream defects by 80% while removing 160+ manual hours per month. I also developed autonomous GPT agent workflows to orchestrate Selenium and PyAutoGUI across GHX, Lawson, and SAP, cutting analyst data-entry time by 75% and eliminating 90% of human errors. I currently lead a team of engineers to deploy AI-driven pipelines, including RAG cleaning and data-migration workflows, exposing LLM-callable Python modules across multiple portals with robust cross-system accuracy. My work improves governance, SLA performance, and operational resilience across hospital networks while driving cost savings and scalable delivery.

Available to hire

I am a machine learning engineer focused on building scalable data platforms in healthcare. I architected an enterprise health care data normalization platform using LangChain and OpenAI embeddings, processing 2M+ GHX records per month with 95% entity-resolution accuracy and reducing downstream defects by 80% while removing 160+ manual hours per month. I also developed autonomous GPT agent workflows to orchestrate Selenium and PyAutoGUI across GHX, Lawson, and SAP, cutting analyst data-entry time by 75% and eliminating 90% of human errors.

I currently lead a team of engineers to deploy AI-driven pipelines, including RAG cleaning and data-migration workflows, exposing LLM-callable Python modules across multiple portals with robust cross-system accuracy. My work improves governance, SLA performance, and operational resilience across hospital networks while driving cost savings and scalable delivery.

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Experience Level

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Language

Javanese
Advanced

Work Experience

Machine Learning Engineer at Bio-Med Services, Inc (Prime Healthcare)
August 1, 2024 - November 18, 2025
Architected enterprise health care data normalization platform using LangChain and OpenAI embeddings; processed 2M+ GHX records per month with 95% entity-resolution accuracy, reducing downstream defects by 80% and removing 160+ manual hours per month. Developed autonomous GPT agent workflows to orchestrate Selenium and PyAutoGUI across GHX, Lawson, and SAP, cutting analyst data-entry time by 75% and eliminating 90% of human errors. Led a 5-engineer team to deploy a RAG cleaning pipeline (SQL, 768-dim vectors) achieving 94% matching accuracy and improving BI reporting SLA from 48 to 19 hours across 42 hospital facilities. Engineered AI-driven supplier‑chain automation exposing Python modules as LLM-callable tools with structured JSON interfaces, maintaining 99.97% cross-system sync accuracy across 4 portals. Directed LLM-assisted data migration for 8 hospital onboarding tasks, automating catalog mapping, NER extraction, and validation workflows with zero data-loss incidents. Implement
Lead Software Engineer at Easley Dunn Productions Inc
March 1, 2025 - March 1, 2025
Directed end-to-end development of an enterprise project management platform, leading a 4-developer team to deliver a production-ready MVP two weeks early. Engineered scalable React architecture using Context API + useReducer, optimizing 15+ components with React.memo to reduce re-renders by 65% and raise UI quality score from 62 to 94. Managed agile sprint cycles, improving story throughput by 40% and achieving 95% sprint goal completion. Built an A/B testing framework that improved user task completion from 67% to 91% and implemented a predictive work‑load balancing module using Python and lightweight ML models to analyze task history, increasing sprint capacity planning accuracy by 28% and reducing bottlenecks.
Full Stack Developer at Borde.io
August 1, 2024 - August 1, 2024
Integrated gravitational teleport authentication to enforce secure role-based access across 50+ Linux servers, reducing incident response time by 60% for a 15-person DevOps team. Automated SSH session workflows in Python, reducing server onboarding time from 45 minutes to 6 minutes (87% improvement) and eliminating 90% of time-out failures. Built automated login intelligence scripts using Python and regex to detect anomalous SSH behavior across 50+ servers, reducing manual triage time by 70% and improving observability. Designed resource-usage profiling to baseline CPU/memory behavior for remote workloads, enabling early detection of degraded nodes and improving system stability under peak load by 35%.

Education

Master of Science, Computer Science at University of Southern California
January 11, 2030 - November 18, 2025

Qualifications

Add your qualifications or awards here.

Industry Experience

Healthcare, Software & Internet, Professional Services, Life Sciences