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Vetted Azure Machine Learning Professionals
Pre-screened and vetted.
Mid-level AI/ML Engineer specializing in Generative AI and NLP
Mid-level Full-Stack Developer specializing in cloud-native microservices
Senior Computer Vision Engineer specializing in medical imaging and MLOps
Mid-level AI/ML Engineer specializing in predictive maintenance, computer vision, and LLM/RAG systems
Mid-level AI/ML Engineer specializing in NLP and MLOps for regulated industries
Mid-level AI/ML Engineer specializing in cloud ML, real-time pipelines, and graph neural networks
Senior AI/ML & Data Science professional specializing in NLP, LLMs, and MLOps
Mid-level AI/ML Engineer specializing in MLOps, NLP/CV, and fraud detection
Senior AI/ML Engineer specializing in LLMs, NLP, and production MLOps
Mid-Level Generative AI Engineer specializing in LLM apps, RAG, and cloud deployment
Mid-Level Software Engineer specializing in Java microservices and cloud-native platforms
Senior Data Scientist and AI Engineer specializing in NLP, LLMs, and MLOps
Senior AI Architect specializing in Generative AI and LLM systems
Mid-level AI Engineer specializing in production LLM, RAG, and agentic AI systems
Senior Data Scientist specializing in NLP, MLOps, and cloud ML platforms
Chris Harry Patrick
Mid-level AI/ML Engineer specializing in healthcare, risk modeling, and MLOps
“Robotics software engineer who built a ROS Noetic-based perception-to-control stack for a pick-and-place robotic arm, integrating OpenCV/TensorFlow vision with motion planning and PID tuning. Demonstrated strong real-time debugging skills (rosbag, queue/latency fixes) and experience deploying reproducible robotics environments with Gazebo simulation, Docker, and GitLab CI.”
Pravallika Kilari
Mid-level AI/ML Engineer specializing in NLP, GenAI, and MLOps in healthcare and finance
“AI/ML engineer with CVS Health experience deploying production LLM systems in regulated healthcare settings, including a large-scale RAG solution (1M+ documents) built for compliance-grade, auditable policy/regulatory Q&A with strong anti-hallucination controls. Also delivered an NLP summarization system for physician notes/case narratives by partnering closely with non-technical care operations stakeholders and iterating via prototypes, dashboards, and feedback loops.”