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Peloton // connected indoor fitness cycles
Engineering, Full Time    New York City    Posted: Friday, February 19, 2021
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The Role

The Artificial Intelligence team at Peloton is looking for a machine learning data scientist to drive our AI applied research for connected fitness. Their main focus will be to optimize the connected fitness platform through research & application of AI & ML techniques. They will work closely with ML Engineers & Data Analysts to transfer technology from the concept phase into translation & deployment phases. Were looking for someone whos passionate about the future of fitness & is excited about the challenges of AI & machine learning for the connected future.


  • Research & apply best-in-class machine learning techniques for time series motion & other fitness-related data.
  • Enhance & develop solutions with a heavy focus on performance & efficiency running on embedded, resource constrained hardware.
  • Collaborate & work closely with engineers to translate & deploy new AI/ML solutions for connected fitness devices.
  • Collaborate & work closely with data infrastructure teams to design, test, verify, & implement machine learning models that impact the daily life of millions of users.
  • Specifically, you may encounter projects focused on: Using Bayseian methodologies on time series, Hidden Markov Models, LSTM, RNN, Feature extraction, Filtering, etc.


  • Strong understanding in highly quantitative fields including Computer Science, Machine Learning, Operational Research, Statistics, Mathematics, etc.
  • Experience with ML fields, e.g., statistical learning theory, probabilistic graphical modeling, natural language processing.
  • 2+ years of industry experience in predictive modeling, data science, & analysis.
  • Experience in an ML engineer or Data Scientist role building & deploying ML models.
  • Experience writing code in Python, R, C/C++ with documentation for reproducibility.
  • Experience handling terabyte size datasets, diving into data to discover hidden patterns, using data visualization tools, writing SQL, & developing & optimizing models.
  • Experience writing & speaking about technical concepts to business, technical, & lay audiences & giving data-driven presentations.
  • Comfortable working with both batch & near real-time applications.

Please note: This is a full-time position that will be remote initially (due to COVID-19) & based in our NYC HQ once safe to re-open the office.

About Peloton 

Founded in 2012, Peloton is a global interactive fitness platform that brings the energy & benefits of studio-style workouts to the convenience & comfort of home. We use technology & design to bring our Members immersive content through the Peloton Bike, the Peloton Tread, & Peloton Digital, which provide comprehensive, socially-connected fitness offerings anytime, anywhere. We believe in taking risks & challenging the status quo by continuously innovating & improving. Our team is made up of passionate brand ambassadors, & we know that together, we go far.

Headquartered in New York City, with offices, warehouses & retail showrooms in the US, UK & Canada, Peloton is changing the way people get fit. Peloton has been named to many prestigious industry lists, including Fast Company's Most Innovative Companies, CNBC's Disruptor 50, Crain's New York Business' Tech25 & Fast50, as well as TIME's Genius Companies. Visit to learn more about joining our team.

Together We Go Far means that we are greater than the sum of our parts, stronger collectively when each one of us is at our best. In order to be the best version of Peloton, we are deeply committed to building a diverse workforce & inclusive culture where all of our team members can be the best version of themselves. This work has no endpoint; it is the constant work of running an organization that strives to reach its full potential. As a first step in our commitment, we announced the Peloton Pledge to invest $100 million over the next four years to fight racial injustice & inequity in our world, & to promote health & wellbeing for all, from the inside out.

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