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Machine Learning Infrastructure Engineer – Full Stack – CV
| Company | Peloton |
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| Location | Santa Clara, CA, USA |
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| Salary | $176748 – $229772 |
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| Type | Full-Time |
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| Degrees | |
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| Experience Level | Mid Level, Senior |
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Requirements
- 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.
- 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.
Responsibilities
- 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.
Preferred Qualifications
- Experience with C, C++, Java, Swift, or more general purpose programming languages is a plus.
- Interested in picking up new tools/technologies required for development.
