Machine Learning and Signal Processing Engineer (機器學習與訊號處理工程師)
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Summary
Develops and improves core ML and signal-processing algorithms (adaptive and learning-based filtering) for FaceHeart's non-contact physiological sensing software aimed at medical-grade vital sign diagnostics, including experiment design, ablation studies, and formal documentation for certification. Core stack: Python, C/C++, DSP, and ML.
About the job:
We are seeking a strong technical machine learning engineer to develop advanced algorithms for healthcare applications. FaceHeart aims to improve the reliability of non-contact physiological signal sensing and diagnosis and to achieve medical level precision.
What you will be doing:
- Develop and improve the core algorithms, including adaptive filtering, learning-based filtering, etc.
- Develop algorithms for healthcare applications.
- Design and implement comprehensive experiments and evaluation metrics for ablation study to carefully validate the performance and limitations of the software.
- Employ machine learning and statistical techniques to refine the boundary conditions of the software.
- Write formal technical documents for certification.
What we need to see:
- MS or Ph.D. in Computer Science, Electrical Engineering, etc, or having equivalent experience.
- Excellent knowledge of fundamental theory and practice of digital signal processing, pattern recognition and statistical analysis.
- Excellent English writing skills.
- Excellent communication skills.
- Excellent programming skills in Python and C/C++.
Way to stand out from the crowd:
- Experience with image processing and computer vision.
- Experience with multi-thread programming is a plus.
- Be familiar with version control tool (Git/GitLab).