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Staff Applied Machine Learning Scientist

whoopBoston, MASensor Intelligence
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Salary
$170K – $230K
Job type
Full-time
Experience
Senior · 7+ yrs
Posted
6 Oct 2026
Status
Open · checked 7d ago

About this role

This position suits an experienced quantitative scientist with a strong background in machine learning and signal processing who wants to build production-ready edge algorithms for wearable devices. The role is based in Boston, Massachusetts, at WHOOP.

Role Overview

WHOOP seeks a Staff Applied Machine Learning Scientist in Boston, MA, to create and refine production-ready edge algorithms that convert raw sensor data into real-time physiological insights. The professional in this position will handle complex algorithmic challenges by blending deep learning, machine learning, and signal processing methods to improve wearable platform accuracy, latency, power, and scalability.

Key Responsibilities

Build advanced algorithms using signal processing, physiological modeling, machine learning, and deep learning for multimodal sensor and physiological time-series data.
Oversee the creation and ongoing refinement of production-ready edge algorithms that generate reliable, real-time physiological insights from multimodal sensor inputs.
Review large-scale wearable sensor datasets to pinpoint performance gaps, spot challenging conditions, and guide data-backed algorithm enhancements.
Establish strict evaluation methodologies, validation frameworks, and performance metrics for assessing algorithms across all development phases.
Tune algorithms for embedded deployment while balancing accuracy, power, memory, compute, and latency constraints on wearable platforms.
Determine technical direction and set best practices for algorithm development, modeling, experimentation, and validation.
Drive ambiguous, high-impact technical projects starting from research and prototyping through production deployment and monitoring.
Partner alongside Data Science, Firmware, Software, Hardware, Product, and domain teams to turn algorithmic breakthroughs into member-facing features.
Track developments in deep learning, machine learning, signal processing, edge AI, and physiological sensing to build new capabilities.

Requirements

MS or PhD in Biomedical Engineering, Electrical Engineering, Computer Science, Machine Learning, Applied Mathematics, or a related quantitative field.
At least 7 years of professional experience building and deploying signal processing, machine learning, and deep learning algorithms for real-world use cases.
Technical expertise in modern deep learning and machine learning methods tailored for time-series and multimodal sensor data.
Background in digital and statistical signal processing, combining classical techniques with learning-based approaches.
Proficiency in Python for data analysis, experimentation, and algorithm prototyping.
Demonstrated capability to build robust models using large, noisy, real-world datasets that generalize well across diverse conditions.
Experience designing experiments, tracking metrics, conducting error analysis, and translating results into algorithm updates.
Track record of taking algorithms through the complete development lifecycle from research to production monitoring.

Nice to Have

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

Skills and Tools

Python
C/C++
Machine Learning
Deep Learning
Signal Processing
Edge AI

About the Company

WHOOP designs wearable technology that gathers physiological data to give members actionable insights regarding their recovery, training, and sleep. The organization operates on a mission to unlock and inspire performance for life.

How to Apply

Interested candidates should apply on the official company careers page.

Skills and tech stack

PythonC/C++Machine LearningDeep LearningSignal ProcessingC++

Questions candidates ask

Where is this job located?

This role is based in the WHOOP office located in Boston, MA, and candidates must be prepared to relocate if necessary.

What education level is required for this role?

Candidates must hold an MS or PhD in Electrical Engineering, Biomedical Engineering, Computer Science, Machine Learning, Applied Mathematics, or a related quantitative field.

How many years of experience are required?

The position requires 7+ years of experience developing and deploying machine learning, deep learning, and/or signal processing algorithms for complex real-world applications.

What programming languages are mentioned in the posting?

Python is required for algorithm development and data analysis, while experience with C/C++ is highly desirable.

What is the primary focus of the algorithms built in this role?

The focus is on developing production-ready edge algorithms that transform multimodal sensor data into accurate, reliable, and real-time physiological insights while optimizing for accuracy, power, latency, and scalability.

Ready to apply?

The application is on the official whoop careers page.

Apply on company site