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Vetted AI & Machine Learning Professionals in the Charlotte Metro
Pre-screened and vetted in the Charlotte Metro.
Bhargav Gopal
Mid-level Machine Learning Engineer specializing in MLOps and scalable ML pipelines
Varsha Ravula
Mid-level AI/ML Engineer specializing in GenAI, RAG, and cloud-native ML platforms
Ramya Vunikili
Senior Machine Learning Engineer specializing in NLP, Generative AI, and healthcare/legal AI
Avinash Pancheneni
Mid-level Machine Learning Engineer specializing in fraud detection and LLM applications
“Unreal Engine UI engineer focused on scalable, production-ready UI architecture (C++/Slate/UMG/CommonUI) with strong designer enablement via decoupled, interface-driven patterns and MVVM. Demonstrated measurable performance wins: replaced 200+ per-frame Blueprint bindings to cut UI prepass/paint from 4.2ms to 0.5ms and reduced VRAM by ~120MB using texture streaming proxies.”
Mallikarjuna Palla
Mid-level Software Engineer specializing in AI-driven backend and full-stack FinTech systems
Venkata Mahalakshmi Vishnumolakala
Mid-level Software & ML Engineer specializing in cloud data platforms and MLOps
Pravalika Kasojjala
Mid-level AI/ML Engineer specializing in LLM, RAG/GraphRAG, and fraud analytics
“LLM/agent engineer who has deployed a production internal assistant to reduce employee inquiry resolution time while maintaining regulatory compliance. Experienced with RAG, hallucination risk triage, and graph-based orchestration (LangGraph) for enterprise/banking-style workflows, emphasizing schema-validated, citation-backed, tool-constrained agent designs and tight collaboration with non-technical business/compliance stakeholders.”
Suraj Maharjan
Senior Full-Stack Java Engineer specializing in AI/LLM automation and regulated systems
Sai Ravi Teja Grandhisila
Mid-level AI/ML Engineer specializing in production ML, NLP/LLMs, and risk & automotive analytics
Nikshitha Aella
Mid-level Full-Stack Software Engineer specializing in AI platforms and microservices
“Backend engineer currently building an AWS Lambda/FastAPI inventory recommendation system using a LangChain + GPT-4 RAG pipeline and MongoDB vector search; drove major cost optimization via Redis caching (60% reduction) while sustaining 10k+ daily requests under 2s latency. Previously deployed Node.js microservices on AWS OpenShift with Jenkins/Helm at UnitedHealth Group and led a zero-downtime monolith-to-microservices migration at Verizon, including RabbitMQ-based real-time messaging with DLQs and idempotency.”
Koushik Gunjala
Senior AI Engineer specializing in Agentic AI and distributed systems
“LLM/agentic workflow engineer with healthcare domain experience who built a HIPAA-compliant multi-agent RAG system for clinical review automation at UnitedHealth Group, achieving 92% precision and cutting latency 40% through async orchestration and Redis semantic caching. Also has strong data engineering orchestration background (Airflow on AWS EMR with Great Expectations) and a proven clinician-in-the-loop feedback process that improved model faithfulness by 18%.”
Jeevan Vikkurty
Mid-level Generative AI Engineer specializing in LLMs and RAG
Akash Shanmuganathan
Mid-level GenAI & Data Engineer specializing in agentic AI systems and AWS Bedrock
“At onedata, built and deployed an LLM-powered, multi-agent analytics platform on AWS Bedrock that lets users create Amazon QuickSight dashboards through natural-language conversation, cutting dashboard build time from ~30 minutes to ~5 minutes. Strong in production concerns (observability, token/cost tracking, model tradeoffs) and in bridging business + technical work, owning pre-sales pitching through delivery with an engineering management background focused on AI product management.”
Udheep V
Mid-level AI Engineer specializing in Generative AI, RAG, and agentic workflows
Govind Kummari
Senior Machine Learning Engineer specializing in Search, Recommendations, NLP and RAG
Srinivas Peri
Mid-level Robotics & Computer Vision Engineer specializing in GPS-denied autonomy
Praveen Dommalapati
Mid-level AI/ML Engineer specializing in GenAI, RAG, and agentic multi-agent systems
Sree Manasa Vuppu
Mid-level AI Engineer specializing in Generative AI, LLMs, and RAG
“Internship at Discovery Education building a production LLM/RAG chatbot that let marketing and sales teams query and interpret Looker/BI dashboards in natural language, with responses grounded in compliance and state education standards. Emphasizes rigorous evaluation (faithfulness/precision/recall/latency) plus user-feedback analytics, and used LangChain for orchestration, chunking/context-window control, and integration with enterprise sources like SharePoint.”
Pranav Mishra
Junior Machine Learning Engineer specializing in LLM agents, RAG, and MLOps
“AI/ML engineer who has shipped production systems across computer vision and conversational agents: built a YOLOv8-based wheel fitment pipeline at a Techstars-backed automotive startup, focusing on sub-second latency, monitoring, and robust fallback mechanisms that drove 2–3x page view growth and +5–6k users. Also built a voice-based interview platform orchestrating Deepgram + GPT-4 Mini + OpenAI TTS with FSM-driven reliability, and has hands-on RAG experience (LangChain, hybrid retrieval, cross-encoder reranking, custom pseudo-query generation).”