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Vetted AI & Machine Learning Professionals in the DFW Metroplex
Pre-screened and vetted in the DFW Metroplex.
Senior AI and Full-Stack Engineer specializing in LLM-powered microservices
Senior AI/ML Engineer specializing in LLM, NLP, and production ML systems
Bhavana G
Mid-level GenAI Engineer specializing in AI agents and RAG systems
“Built and deployed a production LLM-based RAG agent platform adopted by multiple business teams (Marketing, GTM, Recruiting, Customer Support) to automate knowledge search, Q&A, and content generation. Emphasizes production-grade reliability (grounding/validation/guardrails), rigorous evaluation/monitoring, and cost-aware scaling via model tiering, prompt/retrieval optimization, and caching using LangChain/LangGraph orchestration.”
Asvad Shaik
Mid-level AI/ML Engineer specializing in Generative AI, RAG, and NLP
“Backend engineer who built and migrated a large-scale document intelligence platform used by legal, healthcare, and insurance clients, processing millions of pages. Experienced moving from a monolithic, LLM-heavy approach to a modular FastAPI service architecture with ML classification + RAG, strong validation/auditability, and enterprise security (JWT/OAuth, RBAC, PostgreSQL RLS) with zero-downtime incremental rollouts.”
Fernando Mosqueda
Senior AI/ML Engineer specializing in healthcare AI and MLOps
“Healthcare AI engineer with hands-on ownership of production ML and LLM systems at McKesson, spanning clinical risk prediction and RAG-based documentation tools. Stands out for combining deep clinical-data experience, HIPAA-aware deployment practices, and measurable impact through reduced readmissions, clinician workflow gains, and 20% to 30% faster ML delivery for engineering teams.”
Muaaz Syed
Mid-level AI/ML Engineer specializing in NLP and conversational AI
“ML/NLP engineer focused on real-time IT ops analytics, building a predictive maintenance/anomaly detection platform end-to-end (multi-source ETL, streaming, modeling, and production deployment on GCP/Vertex AI). Uses deep learning (LSTMs, autoencoders/VAEs) plus embeddings (SentenceBERT) and vector search to improve incident correlation and search, citing ~40% reduction in duplicate alert noise.”
Mid-level Data Analyst and AI Engineer specializing in NLP, RAG, and BI analytics
Principal AI/ML Engineer specializing in credit risk and healthcare predictive modeling
Junior Generative AI Engineer specializing in LLM agents, RAG, and multimodal AI
Mid-level AI/ML Data Engineer specializing in cloud data platforms and Generative AI
Senior AI/Robotics Engineer specializing in GenAI, LLM serving, and computer vision
Senior AI Engineer specializing in Generative AI, RAG, and agentic LLM platforms
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and scalable inference
Mid-level Machine Learning Engineer specializing in MLOps, NLP, and real-time data pipelines
Senior GenAI Engineer specializing in enterprise LLM systems and RAG platforms
Mid-level Data Scientist / ML Engineer specializing in risk, fraud, NLP and recommender systems
Mid-level Full-Stack GenAI/ML Engineer specializing in agentic AI and RAG systems
Mid-level Machine Learning Engineer specializing in forecasting, NLP, and MLOps