Deep Learning and Computer Vision Embedded Software Engineer
瀏覽人數: 404
投遞人數: 2
工作類型: 全職
經驗需求: 不限
薪資範圍: 面議
刊登日期: 2021-06-22 13:49:35
有效期限: 2022-01-01

Job Description:

We are dedicated in providing hardware acceleration using the iCatch Neural Network Engine SOC to enable real time, low power and high performance execution of Deep Learning workloads.

Running the models on PC is easy to deal with. It is more challenging to run the models on an edge platform. In this job, you can see the models used in REAL projects instead of just the experiments in laboratory. You will port, debug, and optimize latest state-of-the-art neural network models on iCatch platform. You will also work with hardware designers to tackle functional issues and customer support engineers to help resolve project's deficiencies. Are you interested in this job? Don’t be hesitated. Contact with us!

About iCatch Technology, Inc.

芯鼎自成立以來即放眼全球市場, 追求高品質與設計令使用者驚豔的影像 SoC 為宗旨. 與全球不同應用的品牌與設計公司接軌, 讓芯鼎的開發團隊有更寬廣的視野, 設計出符合不同應用領域的 Soc SDK. 芯鼎基於影像處理與系統整合的核心技術於2017年即推出具有AI處理器的低功耗影像處理 SoC. 目前已有多個品牌公司參與設計, 也有智慧行車紀錄器、AI 影像聯網產品問世. 今年將推出具有更高算力的Edge AI 的多核心 SoC. 更多元的產品應用, 期待具有創意的你一起參與.



  • Support internal teams and external customers on iCatch platforms.
  • Co-work with key AI algorithm developers for deploying on iCatch devices
  • Port, implement, and optimize computer vision algorithms on embedded devices.
  • Deep learning/AI model data preprocess, training & deployment.
  • Evaluate & benchmark state-of-the-art or partner's computer vision solutions


Minimum Qualifications:

  • Bachelor's degree in Computer Science, Computer Engineering or relevant technical field or equivalent practical experience
  • Experience coding in C/C++ and python
  • Know foundations of Deep Learning theory and some practical usage and you worked with any Deep Learning Framework (e.g. TensorFlow, Pytorch, Onnx, Caffe)

Preferred Qualifications:

  • 2 years of embedded development experience
  • Experience with Camera Sensors, ARM and/or other low-power SoC architectures
  • Experience with video or photo post-processing
  • Experience of developing and designing computer vision technologies and systems for running on edge devices


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