SRE & DevOps Engineer (Ray.io)

N-iX is a global software development service company that helps businesses across the world develop successful software products. Founded in 2002, N-iX has come a long way, expanding its presence across Europe, the US, and Latin America. Today, we are a strong community of 2,000+ professionals and a reliable partner for global industry leaders and Fortune 500 companies.

Our client is a global commerce leader where you can influence how the world buys, sells, and gives. You'll be part of a work culture that's been genuinely committed to diversity and inclusion since its founding over twenty five years ago. Here, you can be yourself, do your

best work along with a team of professionals, and have a meaningful impact on people across the globe. We seek people with drive, ideas, and a passion for helping small businesses succeed to help.

About the team : You will join the AI Platform Team, providing highly available, scalable, and automated machine learning infrastructure for researchers and data scientists globally. We are looking for a motivated, self-reliant SRE / DevOps engineer with Python and C++ experience to drive operational excellence, automation, and platform reliability, with a focus on Ray.io.

About the role : This role focuses on maintaining, deploying, and improving AI / ML platform services using Ray.io, with strong emphasis on DevOps, SRE practices, and automation. You will collaborate closely with developers, researchers, and infrastructure teams to ensure robust, scalable, and highly available distributed ML systems.

Responsibilities : DevOps tasks (60%)

• 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.
• Monitor production systems via Ray Dashboard, CLI tools, and integrate alerting / metrics.
• Analyze and resolve production issues, performance bottlenecks, and functional problems.
• Define operational standards, versioning practices, and advise teams on DevOps best practices.
• Prepare documentation, training materials, and provide technical support to platform users.

Development tasks (40%) :

Requirements :

We offer

Skills Required

Airflow, Jenkins, Docker, Linux, Kubernetes, Python