DevOps Engineer (MLOps) - Remote

Overview

The DevOps Engineer (MLOps) will pioneer and mature machine learning operations capabilities, focusing on building robust infrastructure and deployment pipelines in AWS, ensuring seamless collaboration between machine learning and engineering teams.

In Short

• Design and implement scalable CI/CD pipelines for ML models in AWS.
• Establish ML operational best practices in a greenfield environment.
• Collaborate with ML Engineers on infrastructure and deployment strategies.
• Implement monitoring solutions for deployed ML models using Datadog.
• Maintain and optimize ML model repositories for efficient versioning.
• Drive adoption of Infrastructure as Code (IaC) principles.
• Participate in DevOps team ceremonies and planning.

Requirements

• 5+ years of experience in DevOps or MLOps Engineering roles.
• Bachelor’s degree or higher in a related quantitative discipline preferred.
• Deep expertise in AWS infrastructure and services.
• Strong proficiency in Python and key ML libraries.
• Extensive experience with containerization technologies like Docker.
• Experience with ML lifecycle management platforms such as MLflow.
• Ability to thrive in ambiguous environments.
• Excellent collaboration and communication skills.

Benefits

• Flexible working environment with remote options.
• Opportunity to work on cutting-edge ML technologies.
• Collaborative team culture focused on innovation.
• Professional growth and development opportunities.