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Vetted HIPAA Professionals

Pre-screened and vetted.

HG

Mid-Level Software Engineer specializing in backend, data engineering, and Healthcare IT

Queens, NY5y exp
Clerisy Medical P.CQueens College (CUNY)
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AL

Senior Software Engineer specializing in AI-first B2B SaaS and RAG systems

Dallas, TX13y exp
ALFA+Southern Polytechnic State University
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TG

Senior Full-Stack Software Engineer specializing in FinTech and Healthcare IT

Raleigh, NC9y exp
ReddaTech consultingMaharishi International University
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BA

Mid-level Full-Stack Java Developer specializing in FinTech and Healthcare

TX, USA7y exp
Outpace LLCSacred Heart University
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DF

Senior Full-Stack & AI Engineer specializing in FinTech and Healthcare

Princeton, Texas9y exp
NextGen CapitalUniversity of Texas at Dallas
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VN

Mid-level AI/ML Engineer specializing in risk modeling, healthcare analytics, and MLOps

Newark, DE6y exp
University of DelawareUniversity of Delaware
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SL

Senior Data Engineer specializing in Machine Learning and Healthcare Data Platforms

WoodBridge, VA12y exp
Uncommon AnalyticsUniversity of Phoenix
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TA

Senior Full-Stack Engineer specializing in Python, cloud-native SaaS, and data pipelines

United States8y exp
DataStream
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EI

Senior Python Full-Stack Engineer specializing in cloud-native scalable systems

Dover, Delaware8y exp
Verstela
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AS

Senior Backend/Full-Stack Engineer specializing in cloud-native APIs and data platforms

Jacksonville, FL10y exp
Skyline Commerce
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DP

David Pang

Screened

Intern Full-Stack Software Engineer specializing in web apps and healthcare APIs

1y exp
ScriptChain HealthUniversity at Buffalo

Full-stack developer who built an end-to-end e-commerce application with admin/blog/announcement features using Node/Express and AWS S3, emphasizing security via expiring presigned URLs. Also has strong distributed-systems fundamentals from implementing the Raft consensus algorithm (replication logs, majority acks, leader elections) and has created build automation tools (GNU Makefiles/scripts) to streamline team workflows.

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DG

Mid-Level Software Engineer specializing in Healthcare Data Platforms

Remote2y exp
WUDArizona State University

Backend/ML engineer with healthcare domain experience building secure Medicare/Medicaid data APIs and real-time patient risk scoring. Shipped an end-to-end ML pipeline (scikit-learn/XGBoost) served via SageMaker and integrated into Flask APIs, with strong production reliability practices (Kafka schema validation, regression replay, observability, drift monitoring, and human-in-the-loop guardrails).

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LC

Mid-level Full-Stack Engineer specializing in healthcare, mobile apps, and AI

San Jose, CA4y exp
BetterMealUniversity of Texas at Arlington
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LD

Mid-level AI/ML Engineer specializing in LLM-powered RAG systems and MLOps

West Port, CT4y exp
XnodeUniversity of Southern Mississippi
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CT

Mid-Level Backend/API Engineer specializing in AWS and healthcare/first-responder systems

Merced, CA10y exp
Gateway StargazingBremen High School
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KC

Junior Full-Stack Software Engineer specializing in backend APIs and data pipelines

Remote, USA4y exp
Sports MediaUniversity of Houston-Clear Lake
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MA

Junior Software Engineer specializing in Django, data processing, and machine learning

Boston, MA2y exp
Apoth DevelopmentMethodist University
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SB

Junior Machine Learning Engineer specializing in healthcare and IT analytics

Detroit, MI3y exp
HarmonecareUniversity of West Florida
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NA

Junior Full-Stack Software Engineer specializing in scalable web apps and APIs

Kansas City, MO2y exp
Attane HealthUniversity of Central Missouri
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MZ

Entry-Level Software Engineer specializing in healthcare data and AI-enabled tools

Remote0y exp
Mind MenderCalifornia State University, Stanislaus
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AR

Mid-Level Software Engineer specializing in SaaS, mobile apps, and trading automation

Houston, TX6y exp
ITG TechnologiesNorthern Arizona University
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AR

Intern AI/ML & Data Engineer specializing in deep learning, NLP, and cloud data pipelines

USA1y exp
TechMentee, Inc.Pittsburg State University

AI/ML practitioner with production experience building a RAG-powered contextual customer support agent, optimizing for low latency using vector databases and smaller LLMs. Also deployed a fraud detection model on Kubernetes with auto-scaling for heavy transactional loads, and improved chatbot accuracy by 15% through metric-driven testing and evaluation. Partners with Marketing on personalization/recommendation initiatives with measurable outcomes tied to customer feedback.

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