Computer vision and NN ISP algorithm toolchain and optimization engineer
Summary
Develops and optimizes neural network models and toolchains for computer vision and image signal processing (ISP) to run efficiently on edge devices, using frameworks like PyTorch and TensorFlow.
AI Vision Processors For Edge Applications
Our solutions make cameras smarter by extracting valuable data from high-resolution video streams.
Job Description
The engineer will be responsible for the design and development of optimization tools for neural networks, transformers, and large language models (LLMs). This role involves applying post-training, training-aware, and other advanced optimization techniques to enhance model efficiency and performance.
Key responsibilities:
1. Develop optimization toolchains for computer vision models and ISP models (denoising, super-resolution, detail enhancement, etc.).
2. Perform hardware-aware model optimization and porting for Ambarella platforms.
3. Research and evaluate emerging technologies, including pruning, quantization, and fine-tuning techniques for convolutional neural networks (CNNs), transformers, and LLMs.
4. Provide technical support and solutions to customers regarding model optimization and deployment.
Job Requirements:
1. Experience of model deployment would be a plus.
2. Experience of model optimization such as pruning and quantization would be a plus
3. Experience of ISP model fine-tuning would be a plus
4. Experience of model porting would be a plus
5. Background of machine learning based computer vision or ISP knowledge
6. Familiar with machine leaning frameworks like Pytorch, TensorFlow, or Huggingface
7. Skilled in Python and C/C++ programing.