Description

Manage and scale distributed systems and machine learning infrastructure in production environments.

This role is remote.

Responsibilities

• Design, build, and maintain scalable, highly available systems focused on ease of use.
• Configure, deploy, and troubleshoot large-scale production environments.
• Implement alerting, monitoring, and remediation automation within distributed environments.
• Troubleshoot Ray as a service to ensure system stability.
• Optimize ML training and inference through profiling and performance tuning.

Required Skills

• 5+ years of experience working with distributed systems.
• Deep knowledge of computer science fundamentals.
• Hands-on experience with Ray and KubeRay.
• Proficiency in Python, Java, or Go.
• Experience with containerization and orchestration using Docker and Kubernetes.
• Proven track record delivering data and machine learning infrastructure in production.
• B.S., M.S., or Ph.D. in Computer Science, Computer Engineering, or equivalent practical experience.

Preferred Skills

• Experience with ML training and inference profiling and optimization.

Key Skills

Education

Any Gradute