Senior Signal Processing Engineer (Embedded Machine Learning)

RESPONSIBILITIES:

• Partner with firmware and Data Science teams to deploy AI models on edge devices
• Optimize models for inference on edge devices and analyze battery consumption patterns 
• Work with the rest of the Signal Processing team to bring insight and algorithms to personalize the calculations on the device
• Develop innovative and creative algorithms to improve the performance under edge calculation restrictions
• Cooperate in research and explore new features
• Participate in software development, debugging, and validation in order to ensure code and results are production-ready
• Build, train and test machine learning models for big data on the edge
• Collaborate with Product Managers to translate member needs to ML solutions

QUALIFICATIONS:

• Bacheller or Master's degree in applied mathematics, statistics, electrical engineering, biomedical engineering, or related field
• 4+ years of industry or research experience in signal processing and/or machine learning
• Experience developing and implementing AI solutions for real-time processing on edge devices
• Experience collaborating with cross-functional teams to understand requirements and design efficient edge computing solutions
• Experience with biosensor systems and analyzing biomedical data
• Expertise in C and/or Python
• Knowledge of ML libraries like scikit-learn, Tensorflow, PyTorch, Keras, etc.
• Knowledge of statistical method and design of clinical studies
• Strong oral and written interpersonal skills
• Experience with code and battery optimization on the edge is desirable.
• Innovative, knowledgeable, and able to adapt to changing requirements while still producing quality reports with tight deadlines