Key Responsibilities:
Optimize and deploy deep learning models using TensorRT.
Develop and fine-tune AI models using TensorFlow and PyTorch.
Implement object detection and recognition using YOLO.
Work on DeepStream SDK (good to have) for real-time video analytics.
Optimize AI models for edge computing and embedded environments.
Collaborate with the team to integrate AI models with embedded hardware.
Required Skills & Qualifications:
Experience in deploying AI models on NVIDIA Jetson platforms.
Proficiency in TensorRT, TensorFlow, and PyTorch.
Solid understanding of YOLO for object detection.
Good to have experience with DeepStream SDK.
Familiarity with embedded AI development and optimization techniques.
Proficiency in Python and C++ (preferred).
Robust problem-solving skills and ability to work in a team.
Preferred Qualifications:
Previous experience with AI/ML projects related to computer vision.
Knowledge of OpenCV, CUDA, and edge AI deployments.
Understanding of real-time AI inference optimization.
What You Will Gain:
Hands-on experience with NVIDIA Jetson and AI model optimization.
Exposure to real-world AI deployment challenges in embedded systems.
Mentorship from experienced AI and embedded systems professionals.
How to Apply:
Join us and be a part of cutting-edge AI Innovation