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Vetted Machine Learning Engineers in Texas
Pre-screened and vetted in Texas.
Mid-level AI/ML Engineer specializing in Generative AI, RAG, and multi-agent systems
Senior Machine Learning Engineer specializing in LLMs and scalable AI platforms
Mid-level AI/ML Engineer specializing in financial and enterprise machine learning
Mid-level AI/ML Engineer specializing in Generative AI and LLM applications
Junior Machine Learning & Embedded Software Engineer specializing in signal processing and Linux
Mid-level AI/ML Engineer specializing in Generative AI, RAG, and MLOps
Principal Data Scientist specializing in ML governance, healthcare and FinTech risk modeling
Mid-level AI Engineer specializing in Generative AI, LLMs, and RAG
Mid-level AI/ML Engineer specializing in Generative AI, RAG, and multi-agent systems
Mid-level Generative AI Developer specializing in LLM apps and RAG for FinTech and payments
Mid-level Generative AI & NLP Engineer specializing in LLM and RAG applications
Mid-level AI/ML Engineer specializing in healthcare and financial risk systems
Mid-level Generative AI Engineer specializing in LLMs, RAG, and agentic AI
Pavan Punna
Mid-level AI/ML Engineer specializing in LLMs, MLOps, and healthcare-fintech AI
“Built and owned a production GPT-4 RAG assistant for clinical and enterprise query resolution, taking it from initial experiment to deployment, monitoring, and iterative improvement. Their work cut resolution time from 45 minutes to under 2 minutes, achieved roughly 95% accuracy, and scaled to thousands of additional monthly queries while emphasizing safety and trust in a sensitive clinical domain.”
Sujeeth Rajkumar
Mid-level Generative AI Engineer specializing in LLMs and enterprise AI
“Built and owned an enterprise LLM/RAG document intelligence platform for PNC Financial Services in a compliance-heavy environment, focused on grounded answers over internal finance and policy documents. Stands out for combining GenAI product delivery with production engineering discipline, delivering 60% faster document review and materially better answer quality while creating reusable FastAPI-based AI services for multiple teams.”
Sahithi Reddy
Mid-level Machine Learning Engineer specializing in LLM-powered products
“Verizon engineer who productionized an LLM-based personalization capability for a customer-facing digital platform, owning the path from success metrics through scalable APIs, A/B validation, and post-launch monitoring (latency/accuracy/drift). Experienced in diagnosing and fixing real-time LLM/RAG workflow issues under peak load, and in enabling adoption via tailored technical demos/workshops and sales support materials.”
Krishnakaanth Reddy Yeduguru
Mid-level AI/ML Engineer specializing in LLMs, NLP, and MLOps
“AI/ML engineer with healthcare domain depth who led a HIPAA-compliant, production LLM system at McKesson to automate clinical document understanding—extracting entities, summarizing provider notes, and supporting authorization decisions. Hands-on across Spark/Python ETL, Hugging Face + LoRA/QLoRA fine-tuning, RAG, and cloud-native MLOps (Airflow/Kubernetes/Step Functions, MLflow, blue-green on EKS/GKE), with explicit work on PHI handling and hallucination reduction.”
Jaideep bommidi
Senior ML Engineer & Data Scientist specializing in LLM agents, retrieval/ranking, and MLOps
“Machine Learning Engineer currently at Webster Bank building an enterprise-scale LLM agent for Temenos Journey Manager/Maestro, using RAG-style multi-stage retrieval with FAISS/Pinecone, hybrid dense+sparse search, and LoRA fine-tuning optimized via NDCG/MAP and A/B testing. Previously handled messy incident/telemetry data at Deuta Werke GmbH with deterministic + fuzzy entity resolution, and has strong production data engineering experience across Spark/Hadoop and Python ETL systems.”