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Vetted AI & Machine Learning Professionals in Virginia
Pre-screened and vetted in Virginia.
Popular Titles
Navneet Sonak
Staff Machine Learning Engineer specializing in LLMs, recommendations, and MLOps
Ash Kanwal
Senior AI Engineer specializing in LLMs, RAG, and MLOps on AWS
Ziheng Song
Intern Machine Learning Engineer specializing in LLM systems and data analytics
Sai Vasinenku
Mid-level AI/ML Engineer specializing in GenAI, NLP, and MLOps for finance and healthcare
VAISHNAVI CH
Mid-level AI/ML Engineer specializing in LLMs, RAG, and risk/fraud modeling
Vaishnavi Ch
Mid-level AI/ML Engineer specializing in LLMs, RAG, and risk analytics
Bhuvana S
Mid-level AI/ML Engineer specializing in fraud detection, MLOps, and Generative AI
Syed Jafri
Senior Machine Learning Engineer specializing in MLOps, GenAI, and real-time systems
Rajashree Shanmuganathan
Mid-level AI Engineer specializing in GenAI and RAG pipelines
Bala Santhoshi
Mid-level Data Scientist / AI/ML Engineer specializing in NLP, CV, and MLOps in Financial Services
Divya Sree G
Mid-level Generative AI Engineer specializing in LLMs, RAG, and semantic search
Aakash Jadhav
Mid-level Machine Learning Engineer specializing in LLMs and production NLP
Karan Raj Padam Raj
Mid-level AI/ML Engineer specializing in NLP, LLMs, and MLOps
Rayyan Alam
Junior Robotics & Machine Learning Engineer specializing in autonomy and RAG systems
“New-grad robotics software engineer with hands-on ROS 2 autonomy experience (Nav2, SLAM Toolbox, AMCL) and a strong track record debugging real-world instability (QoS, lifecycle timing, sensor dropouts). Built an HRI speech system on a Stretch 3 robot with deterministic, context-aware templates to manipulate trust/competence/emotion conditions, and integrated an LLM high-level planner that outputs PDDL for classical task planning and replanning.”
Abhinav Vengala
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and MLOps
“LLM/agentic systems engineer who built a production "Agentic AI Diagnostic Assistant" for network engineers, using a multi-agent Llama 2 + LangChain architecture with RAG over telemetry/incident data in DynamoDB and confidence-based deferrals to reduce hallucinations. Also has strong MLOps/orchestration experience (Airflow, EventBridge, Spark, Docker, SageMaker/ECS) at multi-terabyte/day scale and delivered multilingual NLP analytics (fine-tuned BERT/spaCy) for support operations through hands-on stakeholder workshops.”
Vikhyat Chauhan
Mid-level Software Engineer specializing in ML systems, robotics, and healthcare imaging
Hrithika Shakelli
Mid-level Software Engineer specializing in Full-Stack and GenAI/ML platforms
Sasi Boyapati
Mid-level AI Engineer specializing in healthcare ML, NLP, and MLOps
Syed Haider
Senior Machine Learning Engineer specializing in GenAI and LLM-powered systems
Shanmukha Jwalith Kristam
Mid-level Data Scientist / ML Engineer specializing in MLOps and Generative AI
“Built and deployed an AI agent to help patients navigate complex housing information by scraping and normalizing unstructured data across all 50 U.S. states, then layering a LangChain RAG system with MMR re-ranking to reduce hallucinations. Experienced in orchestrating multi-agent workflows (LangGraph/CrewAI) and production reliability practices (Pydantic-validated outputs, LLM-as-judge evals, tracing). Also delivered stakeholder-facing explainability via SHAP dashboards for a loan-approval predictive model at Welspot.”
HemaSri Perumalla
Mid-level AI/ML Engineer specializing in fraud detection and healthcare predictive analytics
“ML/AI engineer with production experience in high-scale banking fraud detection at Truist, building an end-to-end pipeline (Airflow/AWS Glue/Snowflake, PyTorch/sklearn) with automated retraining and Kubernetes-based deployment; delivered measurable gains (22% fewer false positives, 15% higher recall) and reduced manual ops ~40%. Also partnered with clinicians at Kellton to deploy an LLM system for summarizing/classifying clinical notes, improving review time and decision speed.”
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.”