Role 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:
. Develop optimization toolchains for computer vision models and large language models (LLMs).
. Perform hardware-aware model optimization and porting for Ambarella platforms.
. Research and evaluate emerging technologies, including pruning, quantization, and fine-tuning techniques for convolutional neural networks (CNNs), transformers, and LLMs.
. Provide technical support and solutions to customers regarding model optimization and deployment.
Requirements:
. Education background: Master degree or degree
. Minimum experience: At least one year of relevant work or academic experience
. Similar or other experiences:
- Experience of model deployment would be a plus
- Experience of model optimization such as pruning and quantization would be a plus
- Experience of LLM fine-tuning would be a plus
- Experience of model porting would be a plus
. Skills
- Background of machine learning based computer vision or LLM knowledge
- Familiar with machine leaning frameworks like Pytorch, TensorFlow, or Huggingface
- Skilled in Python and C/C++ programing.
Computer vision and LLM algorithm toolchain and optimization engineer • Hsinchu, Taiwan
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