AlfredCamera is a mobile application which turns your old, unused smartphones into home security cameras. Alfred's mission is to provide accessible security for everyone. As the most trusted brand in this area, our apps have achieved more than 25M downloads with Android/iOS combined and manages to acquire exceptional user ratings on both platforms. We are determined to create the product with first-class user experiences together with best performance and stability.

【 Your role 】

We are currently looking for skilled, experienced and passionate engineers to support and facilitate the productization of computer-vision and deep-learning technologies. If you think you are the right guy, please don't hesitate and join us!

【 Your Responsibility 】

In this job, you will be responsible for:

- Participate in the productization activities involves computer vision related technologies

- Develop algorithms to fulfill product requirements

- Debug issues in graphics pipeline and optimize execution performance on devices

- Analyze the data collected to locate potential product issues

- Train/Fine-tune machine learning models to meet productization accuracy/performance requirements

- Build prototypes or proof-of-concepts demos on simulated or mobile environments

- Evaluate new technologies/models/services with productization potentials

- Co-work with other teams to facilitate the adoption of related technologies within the company

【 三級防疫警戒期間，面試全程以線上方式進行 】

【 Ideal candidates have 】

- Self-motivated and enthusiastic in deep learning / computer vision technologies
- MS or PhD majored in related areas (Computer Science, EE, Mathematics, and Statistics) is highly recommended
- Solid Python programming skills in terms of data analysis and machine learning
- Familiar with machine learning product development flow, experiences with TensorFlow is highly recommended
  
【 Nice to have 】
- Programming/Development skills on mobile/web platforms is highly recommended
- OpenCV/OpenGL related know-hows is a plus
- Experiences working on features with on-device calculation and performance optimization is a plus

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