Vetted Machine Learning Engineers in the Raleigh-Durham

Pre-screened and vetted in the Raleigh-Durham.

VM

Junior AI/ML Engineer specializing in LLM agents, explainable AI, and computer vision

Durham, North Carolina1y exp
Duke UniversityDuke University

Robotics/computer-vision engineer with industrial safety monitoring experience, building real-time pose estimation (TRTPose) and 2D-to-3D localization and optimizing pipelines to sustain 30+ FPS under heavy multi-entity load. Also brings edge-to-cloud distributed systems work (HoloLens + Google Vision/Translation) and production ML deployment experience using Docker/CI/CD across finance and edge camera environments.

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MS

Junior Software Engineer specializing in AI agents and LLM integrations

Cary, NC2y exp
Fouress Synergy TradingNortheastern University
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JL

Senior Machine Learning Engineer specializing in Generative AI, NLP, and MLOps

North Carolina, US24y exp
MetLifeSan José State University
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Sai Vikas Reddy Yeddulamala - Mid-level AI/ML Engineer specializing in LLMs, RAG systems, and MLOps in NC, USA

Mid-level AI/ML Engineer specializing in LLMs, RAG systems, and MLOps

NC, USA4y exp
Cardinal HealthNorth Carolina State University
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SB

Mid-level AI/ML Engineer specializing in fraud detection, risk modeling, and LLM/RAG systems

Raleigh, NC4y exp
CitigroupNorth Carolina State University
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MS

Intern AI Engineer specializing in LLMs, RAG, and multimodal generative AI

Raleigh, NC1y exp
SignoFiNortheastern University
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SM

Mid-level AI/ML Engineer specializing in GenAI, NLP, and MLOps on cloud

NC, USA4y exp
Cardinal HealthUniversity of North Carolina at Charlotte
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RK

Mid-level AI/ML Engineer specializing in FinTech and production ML systems

North Carolina, USA4y exp
PNCUniversity of Cincinnati
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NG

Junior Machine Learning Engineer specializing in NLP, data pipelines, and LLM workflows

Raleigh, NC2y exp
EcoServantsUniversity of Colorado Boulder

Built and shipped a production LLM-powered decision system that replaced a slow, inconsistent manual review process by turning messy text into structured, auditable outputs behind an API. Demonstrates strong end-to-end ownership of reliability and operations (schema validation, retries/fallbacks, latency/cost controls, monitoring for drift) and a disciplined approach to evaluation and regression testing. Experienced collaborating with non-technical reviewers to define success criteria and deliver interpretable outputs that get adopted.

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SD

Mid-level AI/ML Engineer specializing in LLM systems, MLOps, and real-time fraud detection

NC, USA4y exp
FileTax.comNorth Carolina State University
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