Responsibilities

• Responsible for ensuring our ML systems are operating and running efficiently for large model deployment, training, evaluation, and inference.
• Responsible for the stability of offline tasks/services in multi-data center, multi-region, and multi-cloud scenarios.
• Responsible for resource management and planning, cost and budget, including computing and storage resources.
• Responsible for global system disaster recovery, cluster machine governance, stability of business services, resource utilisation improvement and operation efficiency improvement.
• Build software tools, products and systems to monitor and manage the mL infrastructure and services efficiently.
• Be part of the global team roster that ensures system and business on-call support.

Requirements

Qualifications:

• Bachelor's degree or above, majoring in Computer Science, computer engineering or related fields;
• Strong proficiency in at least one programming language such as Go/Python/Shell in Linux environment;
• Strong hands-on experience with Kubernetes and containers skills, and have ≥3 years of relevant operation and maintenance experience;

Preferred Qualifications

• Possess excellent logical analysis ability, able to reasonably abstract and split business logic, a strong sense of responsibility, good learning ability, communication ability, self-driven and good team spirit;
• Have good documentation principles and habits to be able to write and update workflow and technical documentation as required on time.
• Engage in the operation and maintenance of large-scale ML distributed systems;
• Experience in operation and maintenance of GPU servers.