Vetted OpenCV Professionals

Jeevan Hebbal Manjunath

Screened

Junior Robotics & Machine Learning Engineer specializing in autonomous systems

Tempe, AZ2y exp

“Robotics engineer leading development of a Physical Reservoir Computing controller for a pneumatic soft robotic arm, owning everything from automated data collection and leak-testing automation to hardware design/manufacturing and cross-lab integration with Virginia Tech. Built ROS 2/DDS-based multi-robot systems integrating OptiTrack, a lab quadruped, and a UR5e, and pairs simulation (Gazebo/MuJoCo) + PPO RL training with production-ready tooling (Docker, CI/CD, Flask dashboards, RAG chatbot portfolio).”

“AI/ML engineer with 9+ years of experience building production recommendation and LLM systems end-to-end, from experimentation through deployment, monitoring, and retraining. Stands out for combining strong MLOps discipline with practical GenAI/RAG implementation, including measurable impact such as ~25% higher engagement on an e-commerce recommender and nearly 30% faster knowledge retrieval from internal documents.”

“Built a production-grade clinical and insurance document AI system in a HIPAA/PHI-regulated environment, taking it from experimentation through Azure deployment, monitoring, and iterative improvement. Stands out for translating RAG/LLM research into reliable microservices with strong safety controls, drift monitoring, and human-in-the-loop workflows that cut manual review time by 60-70%.”

“ML/AI engineer with hands-on experience building healthcare and fraud-detection systems from experimentation through deployment, monitoring, and retraining. Stands out for combining real-time IoT pipelines, cloud-native MLOps, and GenAI/RAG in regulated healthcare settings, with reported impact including reduced emergency response times and a 25% reduction in manual diagnosis time.”

Kathan Patel

Screened

Mid-level Generative AI Developer specializing in Python and LLM applications

5y exp

“Currently working on Kavia AI, an end-to-end AI coding platform that lets users generate enterprise applications from prompts and existing codebases via SCM integrations. The candidate has hands-on experience across the GenAI stack—prompt engineering, LangGraph-based multi-agent orchestration, RAG, knowledge graphs, FastAPI, and AWS monitoring—with a focus on making software creation accessible to non-technical users.”