Senior Signal Processing Engineer

Whoop • Boston, MA

1d • $150,000 - $215,000 • Onsite

About The Position

Whoop, Inc. seeks a Senior Signal Processing Engineer in Boston, MA to design and implement algorithms for extracting physiological information from noisy biosensor data and optimizing on-device computation. This role involves partnering with Firmware and Data Science teams to deploy AI and ML models on edge devices, optimizing models for real-time inference, and analyzing battery consumption patterns. The engineer will collaborate with the Signal Processing team to develop personalized algorithms, research innovative solutions for edge-computation constraints, and contribute to software development, debugging, and validation. Building, training, and testing ML models for large-scale edge data processing, and translating member needs into ML-based solutions with Product Managers are also key responsibilities.

Requirements

• Master's degree in Computer Science, Applied Mathematics, Electrical Engineering, Biomedical Engineering, or related field (or foreign degree equivalent)
• At least 4 years of experience with signal processing and/or machine learning.
• At least 4 years of experience developing and implementing AI solutions for real-time processing on edge devices.
• At least 4 years of experience collaborating with cross-functional teams to understand requirements and design efficient edge computing solutions.
• At least 4 years of experience with biosensor systems and analyzing biomedical data.
• At least 4 years of experience with signal and image processing applications (C, C++, Python or MATLAB).
• At least 4 years of experience with ML libraries such as scikit-learn, Tensorflow, PyTorch or Keras.
• At least 4 years of experience with statistical methods and design of clinical studies.
• At least 4 years of experience with code and battery optimization on the edge.
• At least 4 years of experience adapting to changing requirements while producing high quality reports under tight deadlines.

Responsibilities

• Design and implement algorithms to extract physiological information from noisy biosensor data.
• Optimize on-device computation.
• Partner with Firmware and Data Science teams to deploy artificial intelligence and machine learning models on edge devices.
• Optimize models for real-time inference on edge devices, including analysis and improvement of battery consumption patterns.
• Collaborate with the Signal Processing team to develop algorithms that personalize calculations based on member data.
• Research and design innovative algorithms to improve performance under edge-computation constraints.
• Contribute to software development, debugging, and validation to ensure production-ready code and reliable results.
• Build, train, and test machine learning models for large-scale data processing on edge devices.
• Collaborate with Product Managers to translate member needs into machine learning-based solutions.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior