Signal Processing Engineer II

Updated on 11/15/2023

501-1,000 employees

Wearable performance & optimization technology

Company Overview

Whoop’s mission is to unlock human performance though tapping into every individual owner's potential which can be enhanced through continuous monitoring. The company has built a system across hardware, software, and analytics designed to collect and analyze the most important data on the human data.

Consumer Goods

Hardware

Company Stage

Series F

Total Funding

$406.1M

Founded

2012

Headquarters

Boston, Massachusetts

Growth & Insights

Headcount

6 month growth

↑ 16%

1 year growth

↑ 18%

2 year growth

↑ 1%

Locations

Cambridge, MA, USA

Experience Level

Entry

Junior

Mid

Senior

Expert

Desired Skills

Data Analysis

Data Science

Data Structures & Algorithms

Keras

Pytorch

Tensorflow

Python

CategoriesNew

AI & Machine Learning

Requirements

Bachelor's or Master's degree in applied mathematics, statistics, electrical engineering, biomedical engineering, or a related field
A minimum of 2 years of industry or research experience in signal processing and/or machine learning
Strong experience with biosensor systems and analyzing biomedical data
Proficiency in C and/or Python programming languages
Knowledge of adaptive signal processing and time-series analysis
Solid understanding of statistical methods and experience in designing clinical studies
Familiarity with machine learning libraries such as scikit-learn, Tensorflow, PyTorch, Keras, etc
Excellent communication skills, both written and oral, to effectively convey complex technical concepts to diverse teams
Demonstrated ability to think innovatively and adapt to changing requirements while consistently producing high-quality reports within tight deadlines

Responsibilities

Collaborate closely with Data Science and Research teams to enhance user metrics by developing innovative and creative algorithms
Monitor and ensure the proper functioning of algorithms across our diverse user population, addressing any issues related to data and data quality
Validate wearable technology in clinical settings, analyze biomedical data, and prepare comprehensive reports for cross-functional teams
Participate in software development, debugging, and validation processes to ensure code and results are production-ready
Contribute to ongoing research efforts and explore new features to improve the overall performance of our products
Utilize expertise in signal processing and time-series analysis to analyze biosensor systems and optimize their performance
Create and implement mathematical models and machine learning algorithms for processing big data and extracting valuable insights

Desired Qualifications

Experience with wearable technology
Knowledge of physiological data analysis
Experience with clinical studies
Experience with E-verify

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.

As a Signal Processing Engineer at WHOOP, you will be part of a cross-functional team comprised of DSP, Soft Goods, WHOOP Labs, Firmware, and Data Science. You will work on the core, fundamental features at WHOOP. This role will be tasked with solving the incredibly difficult technical problem of obtaining physiological information from noisy sensor data and enhancing diagnostic tools and control methodologies.

RESPONSIBILITIES:

Collaborate closely with Data Science and Research teams to enhance user metrics by developing innovative and creative algorithms.
Monitor and ensure the proper functioning of algorithms across our diverse user population, addressing any issues related to data and data quality.
Validate wearable technology in clinical settings, analyze biomedical data, and prepare comprehensive reports for cross-functional teams.
Participate in software development, debugging, and validation processes to ensure code and results are production-ready.
Contribute to ongoing research efforts and explore new features to improve the overall performance of our products.
Utilize expertise in signal processing and time-series analysis to analyze biosensor systems and optimize their performance.
Create and implement mathematical models and machine learning algorithms for processing big data and extracting valuable insights.

QUALIFICATIONS:

Bachelor’s or Master’s degree in applied mathematics, statistics, electrical engineering, biomedical engineering, or a related field.
A minimum of 2 years of industry or research experience in signal processing and/or machine learning.
Strong experience with biosensor systems and analyzing biomedical data.
Proficiency in C and/or Python programming languages.
Knowledge of adaptive signal processing and time-series analysis.
Solid understanding of statistical methods and experience in designing clinical studies.
Familiarity with machine learning libraries such as scikit-learn, Tensorflow, PyTorch, Keras, etc.
Excellent communication skills, both written and oral, to effectively convey complex technical concepts to diverse teams.
Demonstrated ability to think innovatively and adapt to changing requirements while consistently producing high-quality reports within tight deadlines.

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