Site Reliability Engineer – Machine Learning Systems

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Site Reliability Engineer – Machine Learning Systems

Company Overview
As a global incubator for platforms across commerce, content, entertainment, and enterprise services, ByteDance engages over 2.5 billion users worldwide through products like TikTok. Committed to fostering a safe and positive online environment, ByteDance supports innovation, creativity, and enriching life for people across more than 30 countries with a workforce of over 110,000 employees.

Role Summary
The Machine Learning Systems team supports the development and operation of ByteDance’s distributed ML infrastructure, ensuring stable, reliable, and high-performance systems across global data centers. The role involves managing large-scale AI models and heterogeneous systems, utilizing GPU/NPU/RDMA/Storage integration. Key responsibilities include system stability, resource management, disaster recovery, and on-call support.

Key Responsibilities

• Ensure efficiency and stability of ML systems for large model deployment, training, evaluation, and inference.
• Maintain multi-cloud infrastructure stability and manage resources across multiple data centers and regions.
• Oversee disaster recovery, cluster machine governance, and operations efficiency.
• Develop tools to monitor and manage ML infrastructure and services.
• Provide global on-call support for system and business operations.

Qualifications

• Minimum Requirements:
  • Bachelor’s degree in Computer Science, Computer Engineering, or a related field.
  • Proficiency in programming languages such as Go, Python, or Shell in Linux.
  • Experience with Kubernetes and containers, with at least 3 years in operations and maintenance.
• Preferred Qualifications:
  • Strong analytical and logical skills, a proactive approach, and team spirit.
  • Proficient in technical documentation.
  • Experience in large-scale ML distributed systems and GPU server operations.

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