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Vetted AI & Machine Learning Professionals in the DMV
Pre-screened and vetted in the DMV.
Popular Titles
Akhil Bharadwaj Mateti
Mid-level Software Engineer specializing in Data Science and Machine Learning
“Robotics/AV perception engineer who built a semantic-segmentation road detection system and integrated it into a ROS-based real-time pipeline (ROS bag camera feed to live monitor) achieving ~12 FPS. Strong in practical deployment work: solved multi-library versioning issues (ROS/OpenCV/TensorFlow), containerized the stack with Docker, and optimized inference by shifting runtime to C++ for large latency gains on NVIDIA hardware.”
Junior AI/ML & Full-Stack Engineer specializing in LLM agents and cloud platforms
Intern Machine Learning Engineer specializing in healthcare, cybersecurity, and recommender systems
Principal Engineer specializing in aerospace, defense, and embedded systems
Mid-level AI/ML Engineer specializing in predictive modeling and NLP for healthcare and FinTech
Mid-level AI/ML Engineer & Data Scientist specializing in NLP and production ML
Mid-level AI Engineer specializing in Generative AI and RAG systems
Senior Data Scientist / AI-ML Engineer specializing in LLMs, NLP, and MLOps
Anupreet Singh
Intern Full-Stack Software Engineer specializing in AI and backend systems
“AI intern who built core pieces of Cyberdome, a full-stack agentic compliance automation product using Next.js, Python, RAG, Qdrant, and NIST control retrieval. Stands out for combining frontend product work with backend LLM infrastructure, on-prem/local model deployment, and practical iteration based on user trust concerns around proprietary data.”
Sri Mounika Jammalamadaka
Mid-level AI/ML Engineer specializing in GenAI, LLMs, and data platforms
“Built and helped deploy a production RAG-based LLM assistant for HVAC anomaly diagnostics, partnering closely with field engineers and operations teams to make AI outputs trustworthy in real workflows. Stands out for practical post-launch optimization work—improving retrieval quality, reducing hallucinations, and stabilizing non-deterministic behavior—which contributed to roughly a 40% reduction in diagnosis time.”
Aneri Patel
Junior Machine Learning Engineer specializing in LLM fine-tuning and semantic retrieval
“Backend engineer with legal-tech and AI workflow experience: built JurisAI, an end-to-end legal research system using OCR + embeddings + Pinecone vector search to deliver citation-grounded LLM answers with safe failure modes (~90% recall@K). Also led a GW Law metadata migration into Caspio with batch validation and parallel rollout, and has strong FastAPI/GCP production reliability and observability practices.”
Senior Machine Learning Scientist specializing in forecasting, optimization, and agentic LLM systems
Mid-level AI Engineer specializing in NLP, LLM fine-tuning, and RAG systems
DhanushKautilya Kammaripalle
Junior AI Integration Engineer specializing in LLM agents and RAG on cloud platforms
“Built and deployed LLM-powered features for a startup organizational management application, focusing on real-world deployment constraints like latency and cost. Implemented RAG with FAISS and improved retrieval quality by switching embedding models (OpenAI/Hugging Face) and fine-tuning embeddings on medical corpora for a medical-report UI feature. Uses LangChain and LangGraph to orchestrate multi-node LLM API workflows and evaluates systems with metrics like latency, cost per request, and error taxonomy.”
Siddharth Ranjan
Mid AI/ML Engineer specializing in LLMs, RAG, and cloud AI systems
“Built an AI-powered job matching platform end to end using AWS, Gemini, FastAPI, TypeScript, embeddings, and vector search. The standout result was automating manual matching workflows and scaling resume processing to roughly 2,000 resumes per minute while monitoring quality with F1 score and latency metrics.”
Junior Machine Learning Engineer specializing in LLMs and conversational AI
Mid-Level Machine Learning Engineer specializing in NLP and Generative AI