The AI platform team at Peloton is looking for a Senior Machine Learning Infrastructure Engineer to drive ML infrastructure & operations for the AI/ML teams across Peloton. Their main focus will be to work closely with ML Engineers, data engineers, software engineers & 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 & machine learning engineers focusing on vital tools & infrastructure to support data access, data annotation, model development & deployment pipelines, CI / CD & 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.
- Build, evolve, & scale state-of-the-art machine learning system infrastructure powering Pelotons connected fitness data.
- Work with other machine learning engineers, researchers & backend engineers to implement scalable infrastructure solutions for ML model development, model lifecycle management, model monitoring, data annotation & cleaning.
- Build & maintain CI / CD pipelines to support ML workflows.
- Support ML engineers & researchers with data access software & tooling.
- Collaborate with other ML engineers to build & deploy data stores that support batch pipelines as well as real-time recommendations.
- Expose capabilities that increase the velocity of algorithm & model development, experimentation & deployment.
- 2+ Years of experience developing infrastructure & 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 & self-directed, innovative, biased towards action in fast-paced environments.
- Able to take complete ownership of a feature or project.
- Strong background working with large amounts of time series data, associated annotations & metadata.
- Experience setting up ML CI / CD pipelines, testing & validating code & components, testing & validating data, data schemas, & 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.
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, & streaming technology, we create digital fitness & wellness content & 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 & 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.