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Vetted Machine Learning Engineers in Texas
Pre-screened and vetted in Texas.
Junior ML/Data Engineer specializing in NLP, cloud data pipelines, and real-time sentiment analysis
Junior Machine Learning Software Engineer specializing in cloud-deployed predictive models
sai anuragh Sangoju
Mid-level AI/ML Engineer specializing in fraud detection, credit risk, and NLP
“Built and deployed a production LLM-powered university support chatbot on Azure using a RAG pipeline, focusing on reducing hallucinations, improving latency, and handling ambiguous queries via confidence checks and clarification prompts. Also has hands-on orchestration experience (Airflow/Azure Data Factory), including hardening a demand-forecasting ingestion workflow with sensors, retries, and automated alerts, and uses a metrics-driven testing/monitoring approach for reliable AI agents.”
Mid-level AI Engineer specializing in LLM, RAG, and multi-agent systems
Mid-level AI/ML Engineer specializing in cloud-native data pipelines and RAG systems
Senior Full-Stack Engineer / Technical Lead specializing in cloud-native TypeScript and AI systems
Mid-level GenAI/ML Engineer specializing in RAG, semantic search, and LLM systems
Executive AI Architect specializing in low-power edge/embedded AI systems
Bharat Potluri
Senior Machine Learning Engineer specializing in LLMs, RAG, and agentic AI systems
“LLM/RAG practitioner who has taken a support-ticket triage automation system from prototype to production, building the full pipeline (fine-tuned models, FastAPI inference services, vector storage, monitoring) and delivering measurable impact (~40% reduction in triage time). Demonstrates strong operational troubleshooting of LLM/agentic workflows (observability-driven debugging, fixing agent routing/looping) and supports adoption through tailored demos and sales-aligned technical communication.”
Mid-level Machine Learning Engineer specializing in production ML, MLOps, and LLM retrieval systems
Mid-level AI/ML Engineer specializing in cloud MLOps and real-time data pipelines
Mid-level Machine Learning Engineer specializing in MLOps, GenAI, and financial risk modeling
Mid-level Software Engineer specializing in AI/ML and agentic systems
Junior Generative AI/ML Engineer specializing in LLM automation and RAG systems
Mid-level ML Engineer specializing in FinTech risk, fraud, and GenAI RAG systems
Senior Machine Learning Engineer specializing in document AI and search systems
Mid-level Applied AI Engineer specializing in LLM agents and RAG systems
Vamsi Krishna
Senior Machine Learning Engineer specializing in MLOps and Generative AI
“Built and deployed a production generative-AI copilot at Tungsten that automates invoice/form extraction template creation, reducing weeks of manual model-building work. Combines fine-tuned LLMs (PyTorch/HuggingFace) with OpenCV layout grounding to reduce hallucinations, and runs an end-to-end Kubeflow-based MLOps pipeline with drift monitoring, canary releases, and automated retraining.”
BHAVANA KRISHNAN
Junior AI/ML Engineer specializing in Generative AI, NLP, and MLOps
“LLM engineer who has deployed a production RAG system (LangChain/FAISS/FastAPI) for enterprise semantic search, tackling real-world latency by LoRA/PEFT fine-tuning and grounding outputs with retrieval. Brings strong MLOps (Docker, AWS EKS, CI/CD, MLflow) plus stakeholder-facing explainability experience using SHAP to align ML-driven financial guidance with non-technical domain experts.”
Sam Nick
Senior AI/ML Engineer specializing in Generative AI, LLMs, and NLP
“ML/AI engineer with hands-on experience building healthcare and fraud-detection systems from experimentation through deployment, monitoring, and retraining. Stands out for combining real-time IoT pipelines, cloud-native MLOps, and GenAI/RAG in regulated healthcare settings, with reported impact including reduced emergency response times and a 25% reduction in manual diagnosis time.”