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Machine Learning Infrastructure Engineer

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ABOUT THE ROLE

Peloton’s Artificial Intelligence team is looking for an engineer to drive ML Operations and Infrastructure

for the Deep Learning / Computer Vision team. The role’s focus will be to work closely with ML Engineers

and Data/Infrastructure Engineers to build the connective tissue between the data infrastructure, cloud

platforms, and machine learning systems that would support faster Datasets Access, Model Research,

Continuous Model Training, Generation, and Testing, and smoother Edge Deployment.

YOUR DAILY IMPACT AT PELOTON

Build and evolve state-of-the-art systems and operations pipelines to accelerate productionisation of the team’s ML models.
Work with ML Engineers and Data Engineers to implement scalable solutions for ML model development, model lifecycle management, deployment.
Build and maintain CI / CD pipelines to automate ML model training, testing, and deployment.
Support ML Engineers with Docker and Kubernetes workflows.
Expose capabilities that increase the velocity of algorithm and model development, and Experimentation

YOU BRING TO PELOTON

Hands on experience with developing scalable cloud infrastructure.
Strong programming background, with extensive experience in Python.
Substantial experience with multiple technologies from the following list: AWS, Terraform, Docker, Kubernetes, Sagemaker, MLFlow, Airflow, TensorBoard, Jupyter, MySQL/NoSQL.
Interested in picking up new tools/technologies required for development.
Capacity to work in high growth, fast-paced environments, and can adapt to change.
Experience with C, C++, Java, Swift, or more general purpose programming languages is a plus.
Previous experience with developing machine learning infrastructure.
Strong background working with large amounts of Computer Vision data, associated annotations and meta-data.
Experience setting up ML CI / CD pipelines, testing and validating code and components, testing and validating data, data schemas, and models.
Ability to build full-stack web or mobile applications/services for internal tooling.

#LI-Hybrid

#LI-TP1

The base salary range represents the low and high end of the anticipated salary range for this position based at our Santa Clara office. The actual base salary offered for this position will depend on numerous factors including individual performance, 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

$176,748—$229,772 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.

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.

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Average salary estimate

$203260 / YEARLY (est.)

min

max

$176748K

$229772K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Machine Learning Infrastructure Engineer, Peloton

Are you ready to take your engineering career to the next level? As a Machine Learning Infrastructure Engineer at Peloton in sunny Santa Clara, California, you'll play a crucial role in shaping the future of our Artificial Intelligence team. In this dynamic position, you'll work closely with both ML Engineers and Data/Infrastructure Engineers, creating a bridge between data infrastructure, cloud platforms, and machine learning systems. Imagine building scalable solutions that make accessing datasets faster and enhancing model research, continuous training, and testing processes—ultimately leading to smoother edge deployments. Your daily impact will include crafting state-of-the-art systems and operations pipelines that accelerate the production readiness of ML models. You'll also be responsible for automating processes through CI/CD pipelines, while supporting Docker and Kubernetes workflows. If you love tackling challenges in a high-paced environment, picking up new tools, and have a strong programming background—especially in Python—this is the role for you! You'll also bring experience in cloud infrastructure and dealing with large amounts of computer vision data. Peloton values your wellbeing and offers a competitive salary along with benefits that ensure you can thrive both personally and professionally. So, if you're excited to build impactful solutions and transform the way we work, we want you on our team!

Frequently Asked Questions (FAQs) for Machine Learning Infrastructure Engineer Role at Peloton

What are the responsibilities of a Machine Learning Infrastructure Engineer at Peloton?

As a Machine Learning Infrastructure Engineer at Peloton, your primary responsibilities will include building and maintaining scalable systems for ML model development, CI/CD pipelines for model training, and supporting ML Engineers in Docker and Kubernetes configurations. You'll collaborate closely with ML and Data Engineers to ensure the efficiency of model lifecycle management and deployment. This role is essential in enhancing the velocity of algorithm development and easing experimentation within the ML team.