Machine Learning Infrastructure Engineer

The AI platform team at Peloton is looking for a Senior Machine Learning Infrastructure Engineer to drive ML infrastructure and operations for the AI/ML teams across Peloton. Their main focus will be to work closely with ML Engineers, data engineers, software engineers and data analysts to help support the future of machine learning development in connected fitness. The ML infrastructure engineer will build the connective tissue between the data infrastructure teams and machine learning engineers focusing on vital tools and infrastructure to support data access, data annotation, model development & deployment pipelines, CI / CD and testing. This is a unique opportunity in the industry for someone to build an AI platform that supports both computer vision as well as recommendations problems. 

Responsibilities

• Build, evolve, and scale state-of-the-art machine learning system infrastructure powering Peloton’s connected fitness data.
• Work with other machine learning engineers, researchers and backend engineers to implement scalable infrastructure solutions for ML model development, model lifecycle management, model monitoring, data annotation and cleaning.
• Build and maintain CI / CD pipelines to support ML workflows.
• Support ML engineers and researchers with data access software and tooling.
• Collaborate with other ML engineers to build and deploy data stores that support batch pipelines as well as real-time recommendations.
• Expose capabilities that increase the velocity of algorithm and model development,  experimentation & deployment. 

Qualifications

• 2+ Years of experience developing infrastructure and platforms to power Machine Learning 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, TensorBoard, PyTorch, Jupyter, Kubernetes, MySQL & NoSQL databases.
• Entrepreneurial and self-directed, innovative, biased towards action in fast-paced environments.
• Able to take complete ownership of a feature or project.

Bonus Points

• Strong background working with large amounts of time series data, associated annotations and metadata.
• 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.
• Experience working with large datasets with distributed data processing frameworks like Spark.

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ABOUT PELOTON:

Peloton uses technology + design to connect the world through fitness, empowering people to be the best version of themselves anywhere, anytime. We have reinvented the fitness industry by developing a first-of-its-kind subscription platform. Seamlessly combining hardware, software, and streaming technology, we create digital fitness and wellness content and products that Members love. In 2020 Peloton committed to becoming an antiracist organization with the launch of the Peloton Pledge. Learn more, here.

“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 and 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 and inequity in our world, and to promote health and wellbeing for all, from the inside out.

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