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Vetted Data Scientists in the DFW Metroplex
Pre-screened and vetted in the DFW Metroplex.
Principal AI Architect specializing in GenAI, agentic systems, and RAG
Jisvitha Athaluri
Mid-level AI/ML Engineer specializing in NLP, RAG, and MLOps
“Built a production LLM/RAG-based “model excellence scoring” system at Uber to automatically evaluate hundreds of ML models, standardizing quality assessment and cutting evaluation time from days to minutes on GCP. Also delivered an NLP document classification solution for insurance claims at Globe Life, partnering closely with compliance/operations and improving routing accuracy from ~85% manual to 93% with the model.”
Senior Data Scientist specializing in AI agents and LLM production systems
Mid-level AI Engineer specializing in LLM agents, RAG, and knowledge graphs
Sasi Katamneni
Mid-level Data Scientist / AI-ML Engineer specializing in Generative AI and LLM applications
“Built a production GenAI-powered analytics assistant to reduce reliance on data analysts by enabling natural-language Q&A over Databricks/Power BI dashboards, backed by vector search (Pinecone/Milvus) and a Neo4j knowledge graph, including multimodal support via OpenAI Vision. Demonstrates strong real-world LLM reliability engineering with strict RAG, LangGraph multi-step verification, and Guardrails/custom validators, plus broad orchestration and production monitoring experience (Airflow, ADF, Step Functions, Kubernetes, Prometheus/CloudWatch).”
“GenAI/data engineering practitioner with production experience across Equinix, Optum, and Citibank—built an Azure OpenAI (GPT-4) + LangChain document intelligence platform processing 1.5M+ docs/month and a HIPAA-compliant Airflow healthcare pipeline handling 5M+ claims/day. Also delivered a real-time fraud detection + explainability system using LightGBM and a fine-tuned T5 NLG component, improving fraud accuracy by 15%+ while partnering closely with compliance stakeholders.”
“Built and deployed a production LLM-powered RAG assistant for semiconductor manufacturing failure analysis, reducing engineer triage effort by grounding outputs in retrieved evidence and gating responses with SPC + ML signals (LSTM anomaly scores, XGBoost probabilities). Experienced with LangChain/LangGraph to ship reliable, observable multi-step agents with branching/fallback logic, and evaluates impact using both technical metrics and business KPIs like mean time to triage and downtime reduction.”
Mid-level Data Scientist specializing in LLMs, RAG systems, and production MLOps
Mid-level Data Analyst/Data Scientist specializing in product analytics and machine learning
Mid-level Data Scientist specializing in ML, MLOps, and LLM fine-tuning
Mid-level Data Scientist specializing in financial ML, forecasting, and NLP/GenAI
Mid-level AI/ML Engineer specializing in MLOps, RAG, and production NLP
Senior Data Scientist specializing in ML, analytics, and cloud data platforms
Mid-level Data Scientist specializing in LLMs, RAG systems, and production MLOps
Mid-level Data Scientist specializing in fraud detection and scalable ML systems
Senior Data Scientist specializing in LLM-powered NLP, recommender systems, and anomaly detection
Mid-level AI/ML Engineer specializing in Generative AI, RAG, and multi-agent systems
Senior Data Scientist / ML Engineer specializing in NLP and Generative AI
Mid-level Generative AI Engineer specializing in LLMs, RAG, and agentic AI
Senior Data Scientist specializing in ML, fraud risk, and Generative AI (RAG/LLMs)
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.”