Autonomous Systems Engineer – AI-Powered Decision Making

This AI engineer specializes in autonomous systems and AI-driven decision-making, focusing on robotics, self-driving technology, industrial automation, and smart infrastructure. Their expertise spans reinforcement learning, sensor fusion, real-time AI processing, and predictive modeling to build intelligent machines that operate independently. With experience in top AI frameworks and edge computing solutions, they help organizations develop scalable, real-world automation systems.

• AI-Powered Self-Driving System
  Developed a deep reinforcement learning system for autonomous vehicles, enabling adaptive motion planning and real-time object detection. Integrated LiDAR, RADAR, and camera fusion, reducing collision risks by 40% and improving urban navigation in high-traffic environments.
  
  Autonomous Warehouse Robotics
  Designed an AI-driven robotics fleet for warehouse automation, utilizing computer vision and deep learning to optimize inventory tracking and object handling. Reduced operational errors by 35% and increased fulfillment speed by 50%.
  
  AI-Driven Drone Navigation
  Built an autonomous drone control system with real-time AI decision-making for surveillance and disaster response. Implemented SLAM algorithms and edge AI, enabling drones to navigate dynamic environments with 95% accuracy in object detection.
  
  Smart Traffic Optimization with AI
  Engineered a predictive AI model for city traffic management, analyzing real-time congestion patterns to optimize signal control. Successfully reduced traffic congestion by 25% and improved emergency response efficiency by 30%.
  
  Autonomous Agricultural Machinery
  Developed AI-powered precision farming robots, utilizing computer vision and predictive analytics to optimize planting, watering, and harvesting schedules. Increased crop yield predictions by 30% and minimized resource waste by 20%.