GPU AI Production Systems Engineer

ByteDance; Greater London; On-site; GBP 70,000 - 120,000; Full time

Job summary

ByteDance is seeking a hands-on Production Systems Engineer to manage Linux-based server infrastructure, hardware lifecycle, and automation in global data centers. You will work on deployment, monitoring, and maintenance of large-scale fleets, including GPUs, while collaborating with multiple engineering and operations teams to enhance reliability and efficiency.

The role welcomes engineers across levels, with ownership expanding from hands-on engineering to leading complex global initiatives.

Qualifications

• Bachelor's degree or above in a technical field (CS/CE/EE/IT).
• 2 years of experience in systems engineering or DevOps/SRE roles or equivalent hands-on work.
• Strong Linux administration and troubleshooting foundation.
• Programming or scripting in Python, Bash, Go, or similar for tooling/automation.
• Hands-on experience troubleshooting Linux-based systems, hardware, storage, networking, and performance.
• Sharp analytical and problem-solving skills; quick to learn new tech.
• Good communication and collaboration across teams and regions.

Responsibilities

• Manage deployment, validation, monitoring, maintenance, and lifecycle of large server fleets (CPU/GPU).
• Develop automation scripts and tools to reduce manual workload.
• Troubleshoot Linux systems, hardware, storage, networking, and performance issues.
• Gain experience with AI infrastructure and GPU server platforms; improve tooling and reliability.
• Analyze metrics and hardware data to identify trends and risks; document processes.

Skills

Linux administration

Python

Go

Bash

SRE/DevOps

Hardware troubleshooting

Communication

Education

Bachelor's degree in CS/CE/EE/IT

Tools

Docker

Kubernetes

Redfish

Firmware

BMC

PCIe/NVMe

Job description

ByteDance is seeking a hands-on Production Systems Engineer to manage Linux-based server infrastructure, hardware lifecycle, and automation in global data centers. You will work on deployment, monitoring, and maintenance of large-scale fleets, including GPUs, while collaborating with multiple engineering and operations teams to enhance reliability and efficiency.

The role welcomes engineers across levels, with ownership expanding from hands-on engineering to leading complex global initiatives.