Senior AI/ML Engineer [Embedded Platforms]

Job Requirements

• Design and develop AI/ML based applications with a focus on deployment on embedded hardware platforms(eg: Renesas RZ/V2H, NVIDA Jetson Etc.)
• Port and optimize AI models for real time performance on resource constrained embedded systems
• Perform model quantization, pruning, and conversion (e.g, ONNX, TensorFT, TVM, TFLite, DRP-AI) for deployment
• End to end AI model life cycle development including data preparation, training, validation and inference optimization
• Customize and adapt AI network architectures for specific edge AI use cases(e.g, object detection, classification, segmentation)
• Profile and debug model performance on target embedded boards to meet latency and throughput goals
  

Work Experience

• Minimum 5 years of experience in AI/ML application development.
• Strong Python programming skills, including AI frameworks such as PyTorch, TensorFlow , keras
• Solid experience in developing deep learning based solutions for Computer Vision and Imaging
• Deep understanding of DL architectures like CNN, FCN and their application to visual tasks
• Experience in model optimization techniques such as quantization, pruning, layer fusion and INT8 calibration for edge inference.
• Hands on experience in deploying AI models on embedded platforms
• Proficiency in tools such as OpenCV, ONNX, TVM, TFLite or custom inference engines
• Understanding of system constraints like memory compute and power on edge devices