ABOUT THE ROLE

The AI/CV team focuses on integrating computer vision into fitness products, enhancing the user experience through intelligent coaching and form assessment. We are seeking a Machine Learning Engineer with a passion for developing AI-powered consumer products and a proven track record in computer vision and machine learning.

As a Machine Learning Engineer on Peloton’s Connected Fitness AI team, you will play a key role in developing form feedback systems, advancing activity recognition, enabling intelligent coaching, and analyzing data to generate actionable insights that improve our models.

YOUR DAILY IMPACT AT PELOTON

Provide expertise/guidance to solve problems in the computer vision domain relating to person perception and understanding

Work with other team members to build/train/deploy deep learning models

Hypothesize, design, and conduct various experiments on how we can use novel architectures or new sensors to improve baseline models

Provide help to build tools for model training and diagnostics

Analyze data from alpha and beta testers, as well as production, to assess model performance

Willing to learn and passionate about fitness

YOU BRING TO PELOTON

MS or PhD in Computer Science or a related quantitative field with a focus on computer vision, machine learning and mathematics

Strong background in software engineering

2+ years of experience developing solutions using supervised, self-supervised and unsupervised machine learning techniques in computer vision applications

Deep understanding of various neural network architectures specifically applied to solve CV problems, such as CNN/LSTM/3DConvs/GNN/TCN/Metric Learning and transformer based architectures

Should have a deep understanding of concepts like object detection, segmentation, conditional classification, pose estimation and optical flow

Experience with multiple technologies from the following list: PyTorch, Python, Sagemaker, MLFlow, Airflow, Kubernetes, AWS

BONUS

Prior proven experience on Transformers

Experience with Pose Estimation techniques

Experience with C++ and edge deployment

Experience understanding fairness and bias pertaining to model development

Experience with infrastructure and MLOps

The base salary range represents the low and high end of the anticipated salary range for this position based at our New York City headquarters. The actual base salary offered for this position will depend on numerous factors including, without limitation, experience and business objectives and if the location for the job changes. Our base salary is just one component of Peloton’s competitive total rewards strategy that also includes annual equity awards and an Employee Stock Purchase Plan as well as other region-specific health and welfare benefits.

As an organization, one of our top priorities is to maintain the health and wellbeing for our employees and their family. To achieve this goal, we offer robust and comprehensive benefits including:

Medical, dental and vision insurance

Generous paid time off policy

Short-term and long-term disability

Access to mental health services

401k, tuition reimbursement and student loan paydown plans

Employee Stock Purchase Plan

Fertility and adoption support and up to 18 weeks of paid parental leave

Child care and family care discounts

Free access to Peloton Digital App and apparel and product discounts

Commuter benefits and Citi Bike Discount

Pet insurance and so much more!

Base Salary Range

$176,750—$209,100 USD

ABOUT PELOTON:

Peloton (NASDAQ: PTON) provides Members with expert instruction, and world class content to create impactful and entertaining workout experiences for anyone, anywhere and at any stage in their fitness journey. At home, outdoors, traveling, or at the gym, Peloton brings together innovative hardware, distinctive software, and exclusive content. Founded in 2012 and headquartered in New York City, Peloton has millions of Members across the US, UK, Canada, Germany, Australia, and Austria. For more information, visit www.onepeloton.com.

Peloton is an equal opportunity employer and complies with all applicable federal, state, and local fair employment practices laws. Equal employment opportunity has been, and will continue to be, a fundamental principle at Peloton, where all team members, applicants, and other covered persons are considered on the basis of their personal capabilities and qualifications without discrimination because of race, color, religion, sex, age, national origin, disability, pregnancy, genetic information, military or veteran status, sexual orientation, gender identity or expression, marital and civil partnership/union status, alienage or citizenship status, creed, genetic predisposition or carrier status, unemployment status, familial status, domestic violence, sexual violence or stalking victim status, caregiver status, or any other protected characteristic as established by applicable law. This policy of equal employment opportunity applies to all practices and procedures relating to recruitment and hiring, compensation, benefits, termination, and all other terms and conditions of employment. If you would like to request any accommodations from application through to interview, please email: applicantaccommodations@onepeloton.com.

At Peloton, we embrace technology, including AI, to enhance productivity and accelerate innovation in the work we do for our members. However, in our hiring process, our priority remains in getting to know you and your unique qualifications. To ensure a fair and equitable process, we do not permit the use of AI tools during any stage of the application and interview process. In considering you as an applicant, we want to understand your skills, experiences, and motivations without mediation through an AI system. We also want to directly assess your communication skills without the use of an AI tool.

Qualified applicants with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act, the City of Los Angeles Fair Chance Initiative for Hiring Ordinance and the San Francisco Fair Chance Ordinance, as applicable to applicants applying for positions in these jurisdictions.

Please be aware that fictitious job openings, consulting engagements, solicitations, or employment offers may be circulated on the Internet in an attempt to obtain privileged information, or to induce you to pay a fee for services related to recruitment or training. Peloton does NOT charge any application, processing, or training fee at any stage of the recruitment or hiring process. All genuine job openings will be posted here on our careers page and all communications from the Peloton recruiting team and/or hiring managers will be from an @onepeloton.com email address.

If you have any doubts about the authenticity of an email, letter or telephone communication purportedly from, for, or on behalf of Peloton, please email applicantaccommodations@onepeloton.com before taking any further action in relation to the correspondence.

Peloton does not accept unsolicited agency resumes. Agencies should not forward resumes to our jobs alias, Peloton employees or any other organization location. Peloton is not responsible for any agency fees related to unsolicited resumes.

Machine Learning Engineer III

Job Description

ABOUT THE ROLE