Staff Applied Machine Learning Scientist

What you'll do

• Design and improve algorithms for physiological time-series and multimodal sensor data, including evaluation and validation.
• Optimize algorithms for embedded deployment while balancing accuracy, power, memory, latency, and compute constraints.
• Set technical direction and take initiatives from research and prototyping through deployment, monitoring, and improvement.

What they ask for

• MS or PhD in a related quantitative field.
• 7+ years of experience developing and deploying machine learning, deep learning, and/or signal processing algorithms for complex real-world applications.
• Technical expertise in machine learning and deep learning for time-series and multimodal sensor data, and a strong foundation in digital and statistical signal processing.
• Strong proficiency in Python; experience across the algorithm development lifecycle, including validation, deployment, and continuous improvement.

Nice to have

• Experience with C/C++ and embedded algorithm development.
• Experience with physiological signals, wearable sensors, biomedical sensing, or resource-constrained edge environments.

Pay

$170K – $230K USD base salary

Tools

Python, C/C++

AI focus

Applies machine learning, deep learning, signal processing, and edge AI to wearable sensing and physiological insights; the role also calls for using AI tools in day-to-day work.