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Software Engineer, Machine Learning

At WHOOP, we’re on a mission to unlock human performance. WHOOP empowers its members to perform at a higher level through a deeper understanding of their bodies and daily lives.


  • Build and design tools and infrastructure to support Data Scientists at Whoop as they develop, deploy, and monitor machine learning models. Duties include:
  • Develop and maintain Whoop’s full stack internal toolset including VueJS, Java, Postgres.
  • Work closely with Data Science team members to support model development, training,
  • and monitoring.
  • Contribute to new software feature ideation, planning, and development.
  • Consistently deliver features and PRs with an iterative approach.
  • Follow and introduce best practices around software testing, observability, and monitoring.
  • Perform troubleshooting with logging and monitoring tools such as DataDog, Sentry, and Kibana.


  • Master’s Degree in Computer Science, Data Science, or closely related field, plus 2 years’ experience developing and delivering machine learning models into production, or in the alternative, a Bachelor’s Degree in Computer Science, Data Science or closely related field, plus 5 years’ experience developing and delivering machine learning models into production.
  • Experience, which may have been gained concurrently with primary requirement above, must
  • include 2 years of experience with:
  • Front end development in a modern framework including/ similar to Vue or React,
  • API design and development with languages that include Java, C++, Rust, or Python.
  • Using SQL for relational database design and development.
  • Troubleshooting utilizing AWS Cloudwatch, DataDog, Sentry or Kibana.
  • Utilizing Cloud computing platforms including AWS, Azure, or GCP.
  • Working with data science scripting language of Python or R.
This is a hybrid position working 3 days/week from the company office in Boston, MA and 2 days/week working from home.
WHOOP is an Equal Opportunity Employer and participates in E-verify to determine employment eligibility.

To apply, please visit the following URL:https://jobs.lever.co/whoop/faeef488-7276-47f8-81d9-7087c252345c/apply?lever-source=Job%20postings%20feed→

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