Senior Machine Learning Infrastructure Engineer

The AI/ML organization works on ML-powered consumer products that incorporate computer vision and recommender systems into the fitness domain. We are looking for a Senior Software Engineer to drive ML infrastructure and operations for the AI/ML teams. The main focus will be to work closely with ML Engineers, Data Engineers, Software Engineers, and Data Scientists to help support the future of ML development within connected fitness. The Engineer will build the connective tissue between the data infrastructure and ML teams focusing on vital tools and infrastructure to support model development and deployment pipelines, CI/CD, testing and offline experimentation at scale. This is a unique opportunity in the industry for someone to work on infrastructure and tooling that supports both computer vision as well as recommender systems.

Daily Impact

• Build, evolve, and scale state-of-the-art machine learning system infrastructure powering Peloton’s connected fitness data.
• Work with other ML Engineers, Researchers and Backend Engineers to implement scalable infrastructure solutions for ML model development, model lifecycle management, model monitoring, and offline experimentation.
• Work on building an internal training platform that accelerates the velocity of offline experimentation for ML Engineers.
• Collaborate with other ML Engineers and Data Engineers to build and deploy data stores that support batch pipelines as well as real-time recommendations.

• 2+ years of experience developing infrastructure and platforms to power ML at scale.
• Strong programming background, with extensive experience in Python, experience with C, C++, Java, Swift, or more general purpose programming languages is a plus.
• Substantial experience with multiple technologies from the following list: AWS, MLFlow, Airflow, PySpark, Jupyter, Kubernetes, MySQL & NoSQL databases, Kubeflow.
• Entrepreneurial and self-directed, innovative, biased towards action in fast-paced environments.
• Able to take complete ownership of a feature or project.
• Bonus: Experience setting up ML CI/CD pipelines (Jenkins / GHA), testing and validating code and components, testing and validating data, data schemas, and models.
• Bonus: Experience working with large datasets with distributed data processing frameworks like Spark.
• Bonus: Experience building an internal training platform that supports multiple ML engineers with their offline experimentation.

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 services401k, 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!