Vetted AI & Machine Learning Professionals in Kansas

Pre-screened and vetted in Kansas.

AR

Mid-level AI/ML Engineer specializing in LLM, RAG, and agentic systems

Kansas, KS4y exp
CBREUniversity of Central Missouri
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LL

Mid-level AI/ML Engineer & Data Scientist specializing in NLP and Generative AI

Overland Park, KS5y exp
CenteneUniversity of Central Missouri

Built and deployed an agentic RAG platform at Centene Health to support healthcare claims and complaints workflows (Q&A for claims agents, executive complaint summarization, and compliance triage/classification). Experienced in LangChain/LangGraph orchestration, production deployment on AWS with FastAPI/Docker/Kubernetes, and implementing HIPAA-compliant guardrails to reduce hallucinations and ensure explainable outputs.

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NR

Mid-level AI/ML Developer specializing in MLOps and healthcare predictive modeling

Overland Park, KS3y exp
Tungsten AutomationUniversity of Central Missouri
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AB

Junior AI Engineer specializing in agentic LLM and RAG systems

Overland Park, KS2y exp
EzDataMunchUniversity at Buffalo
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YM

Intern AI/ML Engineer specializing in LLMs, RAG, NLP, and MLOps

Overland Park, USA3y exp
Acclaim LogixUniversity of Central Missouri

Built and deployed a production RAG-based internal document Q&A system using LangChain, vector search, and a dockerized FastAPI LLM service. Focused on reliability by systematically reducing hallucinations and improving retrieval through prompt grounding/abstention strategies, chunking and top-k tuning, and iterative evaluation with logged metrics and manual validation.

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PS

Junior AI/ML Engineer specializing in GenAI, RAG, and full-stack ML systems

Lawrence, Kansas3y exp
University of KansasUniversity of Kansas

Built a university campus assistant chatbot (BabyJ/WWJ) using RAG and agentic routing with a FastAPI + React stack and JWT auth, focusing heavily on production concerns like latency and reliability. Uses techniques like speculative prefetching, smart intent routing, and rigorous eval/testing (golden sets, regression, edge cases) while collaborating closely with campus admin/advising teams to iterate based on real user feedback.

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