Machine Learning Infrastructure Engineer, Full Stack, CV

Peloton • New York, NY

306d • $176,748 - $229,772

About The Position

Peloton's Artificial Intelligence team is looking for an engineer to drive ML Operations and Infrastructure for the Deep Learning / Computer Vision team. The role's focus will be to work closely with ML Engineers and Data/Infrastructure Engineers to build the connective tissue between the data infrastructure, cloud platforms, and machine learning systems that would support faster Datasets Access, Model Research, Continuous Model Training, Generation, and Testing, and smoother Edge Deployment.

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.
• Interested in picking up new tools/technologies required for development.
• Capacity to work in high growth, fast-paced environments, and can adapt to change.
• Experience with C, C++, Java, Swift, or more general purpose programming languages is a plus.
• 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.

Benefits

• Medical, dental and vision insurance
• Generous paid time off policy
• Short-term and long-term disability
• Access to mental health services
• 401k, 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!

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Industry: Miscellaneous Manufacturing