SRE / MLOps Engineer (Ray.io)

TL;DR

SRE / MLOps Engineer (Ray.io): Maintaining, deploying, and improving AI/ML platform services using Ray.io with an accent on DevOps practices and automation. Focus on ensuring robust, scalable, and highly available distributed ML systems.

Location: Remote

Company

hirify.global is a global software development service company that helps businesses across the world develop successful software products.

What you will do

• Design, implement, and maintain CI/CD pipelines for AI/ML platform services.
• Manage and troubleshoot Kubernetes clusters, Docker containers, and cloud infrastructure.
• Ensure high availability (99.999%), system reliability, and security across platforms.
• Automate operational tasks, monitoring, and deployment workflows.
• Deploy and maintain Ray.io clusters, ensuring workload scheduling and distributed job reliability.
• Collaborate with developers to integrate distributed ML pipelines into automated CI/CD workflows.

Requirements

• Strong Python and C++ development experience (2–4 years).
• Hands-on experience with Ray.io: cluster deployment, workload management, distributed task scheduling.
• Familiarity with Ray ecosystem libraries and integration with ML tooling.
• Solid understanding of Kubernetes, Docker, Linux fundamentals, and DevOps practices.
• Fluent in English (spoken and written).