Production System Engineer

About the role

About the Team The Server Management DevOps team is responsible for the end-to-end lifecycle management of servers across ByteDance’s self-built data centers in the United States and Europe. Our scope covers new hardware introduction, data center delivery, production operations, hardware maintenance, configuration and firmware changes, capacity migration, asset decommissioning, data sanitization, and hardware reuse. The team serves as a central coordination point between multiple functions, including: - Hardware New Product Introduction (NPI) - Server and data center operations - Field maintenance and infrastructure management - Hardware vendors and service providers - Supply chain and asset management - Infrastructure platform and automation engineering teams Our goal is to ensure that server infrastructure operates reliably, efficiently, and compliantly at scale throughout its entire lifecycle.

Role Overview We are looking for a hands-on Production Systems Engineer with a strong foundation in Linux systems, server infrastructure, automation, and production operations. This role is open to engineers across a range of experience levels, from early-career engineers with strong technical fundamentals to experienced infrastructure engineers who can take ownership of complex systems and large-scale initiatives. The scope and level of ownership will grow with experience, ranging from hands-on infrastructure engineering and automation development to leading complex global infrastructure initiatives across organizational boundaries

Responsibilities - Server Infrastructure Operations: Assist with the deployment, validation, monitoring, maintenance, and lifecycle management of large-scale server fleets, including CPU and GPU servers. - Automation Development: Develop scripts, tools, and automation solutions using Python, Bash, Go, or other programming languages to reduce manual operational work and improve infrastructure efficiency. - Linux Systems: Work with Linux-based production environments and help troubleshoot operating system, hardware, storage, networking, and performance-related issues. - GPU and AI Infrastructure: Gain exposure to modern AI infrastructure and GPU server platforms, and contribute to operational tooling, validation, monitoring, or reliability improvements. Explore opportunities to apply AI and large language models to infrastructure troubleshooting, automation, knowledge management, and operational decision-making. - Monitoring and Data Analysis: Analyze server health, hardware failures, operational metrics, and infrastructure data to identify trends, risks, and opportunities for improvement. - Technical Documentation: Create and improve technical documentation, standard operating procedures, troubleshooting guides, and internal knowledge bases. - Cross-functional Collaboration: Work with infrastructure engineers, hardware teams, data center operations, platform developers, supply chain teams, and other stakeholders on global infrastructure projects.

Requirements Minimum Qualification(s) - Bachelor's degree or above in Computer Science, Computer Engineering, Electrical Engineering, Information Technology, or a related technical field. - 2 years of experience in systems engineering, infrastructure operations, DevOps, Site Reliability Engineering, or related technical roles, or equivalent hands-on project experience. - Strong foundation in Linux system administration and troubleshooting, with an understanding of basic server architecture, operating systems, storage, networking, and hardware management concepts. - Programming or scripting experience in Python, Bash, Go, or another modern programming language, with the ability to develop tools or automation for infrastructure or operational tasks. - Hands-on experience troubleshooting system, hardware, storage, networking, or performance-related issues in Linux-based environments. - Strong analytical and problem-solving skills, with the ability to learn unfamiliar technologies quickly and investigate complex technical issues in a structured manner. - Good communication and collaboration skills, with the ability to work effectively with engineers and cross-functional stakeholders across different technical domains and regions.