Senior Machine Learning Infrastructure Engineer, AI
New York, NY
The Artificial Intelligence team at Peloton is looking for a Machine Learning Infrastructure Engineer to drive ML infrastructure and operations for the connected fitness AI team. Their main focus will be to work closely with ML Engineers, data engineers, and data analysts to help support the future of machine learning and connected fitness. The ML infrastructure engineer will build the connective tissue between the data infrastructure team and machine learning engineers building vital tools and infrastructure to support data access, data annotation, model generation pipeline, CI / CD and testing.
- 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 Back End engineers to implement scalable infrastructure solutions for ML model development, model lifecycle management, 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
- Expose capabilities that increase the velocity of algorithm and model development and experimentation
- 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, Sagemaker, MLFlow, Airflow, TensorBoard, Anaconda, Jupyter, Kubernetes, MySQL, NoSQL, NFS, Spark.
- Entrepreneurial and self-directed, innovative, biased towards action in fast-paced environments.
- Able to take complete ownership of a feature or project.
- Previous experience with developing machine learning infrastructure.
- Strong background working with large amounts of time series 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.
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.
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