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Vetted pandas Professionals
Pre-screened and vetted.
Amit Prajapati
Junior Data Scientist / Software Engineer specializing in data pipelines and applied ML
“Built a production RAG chatbot for Worcester Polytechnic Institute that indexes 500+ webpages using FAISS + Llama 3, with strong grounding/hallucination controls (confidence thresholds and citations). Also has internship experience orchestrating multi-step ETL pipelines with AWS Step Functions and delivered a 30x faster fraud/claims triage workflow at Munich Re using association rules and stakeholder-friendly dashboards.”
Laxminarayana Yaga
Mid-level AI/ML Engineer specializing in Generative AI, RAG, and MLOps
“Built and deployed a production RAG pipeline at PNC Financial Services to let risk/compliance analysts query millions of internal financial documents in natural language, reducing manual search and speeding regulatory validation. Demonstrates deep practical experience with large-scale document ingestion/OCR cleanup, retrieval performance tuning (hierarchical indexing, caching), and LLM reliability controls (grounding, citations, abstention), plus cloud orchestration on Azure and AWS.”
Nagasaikumar Jampani
Mid-level AI/ML Engineer specializing in Generative AI and RAG pipelines
“AI/LLM engineer with healthcare domain experience who built a production clinical support “chart bot” for Molina, including PHI-safe ingestion of 200k+ PDF policies, vector retrieval, and a fine-tuned LLaMA served via vLLM on ECS Fargate. Demonstrated measurable performance wins (HNSW + namespace partitioning; 30% inference latency reduction) and a rigorous evaluation/monitoring approach, while partnering closely with nurses and operations teams to shape workflows and guardrails.”
Siva Pothuru
Mid-level AI/ML Engineer specializing in LLMs, MLOps, and cloud-native ML
“LLM/agent engineer at USAA who built a production GPT-4o RAG conversational assistant for financial analysts, focused on regulatory interpretation and internal documentation search. Emphasizes compliance-grade reliability with strict grounding, safe fallbacks, and full auditability via MLflow/DVC plus human-in-the-loop review; reports ~45% reduction in ticket resolution time.”
Mid-level Full-Stack Developer specializing in cloud-native microservices and AI/ML integration
Senior Full-Stack Python & AI Engineer specializing in FinTech and real-time platforms
Mid-level Data Scientist specializing in ML and Generative AI (LLMs, NLP, Computer Vision)
Mid-level AI/ML Engineer specializing in generative AI and MLOps
Senior Data Engineer specializing in forecasting, analytics platforms, and BI
Mid-Level Full-Stack Software Engineer specializing in cloud-native FinTech and ERP systems
Mid-level AI/ML Engineer specializing in financial risk, fraud detection, and NLP
Mid-Level Software Engineer specializing in full-stack web development and cloud DevOps
Mid-level AI/ML Engineer specializing in cloud MLOps and scalable model deployment
Mid-level Data Scientist / Machine Learning Engineer specializing in NLP and computer vision
Mid-level Data Scientist / AI/ML Engineer specializing in Generative AI and healthcare analytics
Mid-level Machine Learning Engineer specializing in MLOps and applied data science
Mid-level Full-Stack Software Engineer specializing in GenAI and SaaS platforms
Mid-level AI Engineer specializing in NLP, computer vision, and MLOps