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Develop algorithms for transforming raw sensor data into physiological insights, collaborating with data scientists and engineers to enhance the accuracy and impact of analysis.
At WHOOP, we're on a mission to unlock human performance. WHOOP empowers members to perform at a higher level through a deeper understanding of their bodies and daily lives. Our wearable technology collects rich physiological data, providing members with actionable insights into their recovery, training, and sleep.
We are seeking a Senior Sensor Algorithms Engineer to develop algorithms that transform raw sensor data into meaningful physiological insights. You will work closely with a cross-functional team of data scientists, engineers, and physiologists to design and implement innovative signal processing and machine learning solutions that enhance the accuracy, reliability, and impact of WHOOP’s analytics. Your work will directly contribute to advancing WHOOP’s ability to provide actionable insights to our members, helping them optimize their recovery, training, and sleep.
RESPONSIBILITIES:
- Develop and optimize signal processing and machine learning algorithms to extract physiological metrics from raw sensor data.
- Analyze large-scale wearable sensor datasets to improve accuracy, robustness, and efficiency of existing and new algorithms.
- Collaborate with data scientists, engineers, and domain experts to translate research findings into production-ready features.
- Implement scalable and efficient algorithms for real-time and offline processing of physiological signals.
- Work closely with firmware and hardware teams to ensure seamless integration of algorithms on WHOOP devices.
- Stay up to date with advancements in machine learning, signal processing, and physiological modeling, bringing innovative ideas to WHOOP.
- Validate algorithms through rigorous testing, including lab-based experiments and real-world data analysis.
QUALIFICATIONS:
- MS or PhD in Electrical Engineering, Biomedical Engineering, Computer Science, or a related field.
- 5+ years of experience developing signal processing and machine learning algorithms for time-series data.
- Proficiency in Python and C/C++ for algorithm development and data analysis.
- Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and signal processing techniques.
- Deep understanding of physiological signal processing and time-series modeling.
- Strong analytical and problem-solving skills with the ability to work on complex, ambiguous problems.
- Experience deploying algorithms in production environments, including embedded systems or cloud-based solutions, is a plus.
- Strong commitment to embracing and leveraging AI tools in day-to-day tasks, ensuring AI-assisted work aligns with the same high-quality standards as personal contributions.
Join us in pushing the boundaries of wearable technology and positively impacting people's lives!
This role is based in the WHOOP office located in Boston, MA. The successful candidate must be prepared to relocate if necessary to work out of the Boston, MA office.
Interested in the role, but don’t meet every qualification? We encourage you to still apply! At WHOOP, we believe there is much more to a candidate than what is written on paper, and we value character as much as experience. As we continue to build a diverse and inclusive environment, we encourage anyone who is interested in this role to apply.
WHOOP is an Equal Opportunity Employer and participates in E-verify to determine employment eligibility. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
Top Skills
Machine Learning
Signal Processing
WHOOP Boston, Massachusetts, USA Office
1 Kenmore Sq, Boston, MA, United States, 02215
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