Embedded Computer Vision Engineer

4 weeks ago

Bangalore Urban, India Auric AI Labs Full time
About the Role Auric AI Labs is a well funded next-generation startup dedicated to equipping the Indian warfighter with cuttingedge AI-powered tactical autonomous strike systems. Our mission is to provide a decisive technological edge through innovative, world-class solutions that redefine the future of defense technology.

At Auric AI Labs, we are developing the most advanced vision-based Automatic Target Recognition (ATR) software. This software will be deployed on high-speed, long-range tactical drones to autonomously identify, prioritize, and engage targets in designated mission areas based on user-defined parameters. What You’ll Do Model Development: Design and deploy real-time computer vision algorithms for object detection, recognition, and prioritization. Train machine learning models using diverse imagery datasets to improve detection accuracy and reliability. Optimize algorithms for real-time processing on edge devices with strict SWaP constraints. Testing and Validation: Conduct simulations and field tests to validate system performance in real-world scenarios. Iterate rapidly based on test results and user feedback. Dynamic Features: Implement dynamic target prioritization based on user inputs. Develop visual localization technique to determine the precise location of detected targets. Skills & Qualifications Strong background in computer vision and machine learning frameworks (e.g., TensorFlow, PyTorch, OpenCV). Proficiency in object detection algorithms such as YOLO, SSD, Faster R-CNN, or similar. Experience deploying models on embedded systems like NVIDIA Jetson or Raspberry Pi. Evidence of exceptional ability through work experience, internships, or personal projects. A first-principles approach to solving challenging problems. Why Join Us? At Auric AI Labs, you'll work on cutting-edge AI and defense technologies that make a real-world impact. Be part of a team that tackles extremely challenging problems while shaping the future of autonomous tactical systems.

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