SRE for AI Foundation Infra: GPU Clusters & ML Platform

ByteDance; San Jose (CA); Sur place; USD 140 000 - 210 000; Plein temps

Résumé du poste

ByteDance in San Jose seeks an experienced Seed Infra SRE to sustain stable ML compute infrastructure behind foundation models. You will manage large GPU clusters and distributed training platforms, ensuring reliable deployment and performance.

You’ll collaborate across regions, handle disaster recovery, capacity planning, and on-call support, with hands-on work on Kubernetes, Docker, and cloud resources to optimize utilization.

Qualifications

• 1+ years of experience in DevOps, SRE or infrastructure engineering projects.
• Proficient in at least one or two of Go / Python / Shell in a Linux environment.
• Experience operating resource management and job scheduling systems for distributed systems; familiar with the Kubernetes ecosystem and architecture.

Responsabilités

• Maintain the stable operation of machine learning systems and support the stages of large-model development, training and deployment.
• Manage and plan the company's GPU resources, including cost and budget, across GPU / CPU machines, storage and related resources; provide resource data to support management decisions.
• Drive stability governance for clusters and production services; improve resource utilization and operational efficiency through platform-based, systematic approaches.
• Operate disaster recovery, service deployment and machine lifecycle management across multiple regions and data centers; provide a stable and efficient GPU operating environment.
• Provide operational support for systems and services; participate in troubleshooting of production and system issues.

Connaissances

Go

Python

Shell

Outils

Kubernetes

Docker

Kata

Description du poste

ByteDance in San Jose seeks an experienced Seed Infra SRE to sustain stable ML compute infrastructure behind foundation models. You will manage large GPU clusters and distributed training platforms, ensuring reliable deployment and performance.

You’ll collaborate across regions, handle disaster recovery, capacity planning, and on-call support, with hands-on work on Kubernetes, Docker, and cloud resources to optimize utilization.