云站点可靠性工程师 - DCS云

Our Infrastructure Engineering team supports the company's fast growth by building and operating hyper-scale datacenters, managing the life cycle of server fleet, providing cloud solutions, and developing various infrastructure services and making sure they are scalable and are reliable.

We have three subgroups for this role: - Cloud Host Delivery, Delivery & Standardization - Cloud Host Operation, Operation Efficiency & Reliability

- Design, build, scale, and operate ByteDance’s global infrastructure, including large-scale systems spanning public and private clouds.

- Develop tools, automation frameworks, visualizations, and monitoring systems to streamline operations and drive optimization of global infrastructure.

- Create, manage, and standardize cloud AMIs/images for use across multiple environments, ensuring strict alignment with the company's global compliance standards.

- Thrive in a fast-paced environment, engaging in technical operations and on-call rotations to address incidents related to cloud, OS, network, performance, and reliability.

- Drive improvements across the entire infrastructure lifecycle, from ideation and design through development, deployment, user support, and continuous refinement.

- Bachelor’s degree or above in Computer Science, Software Engineering, Information Security, or a related field.

- Proficient in at least one programming language such as Go, Python, or C++, with solid engineering capabilities in platform development, system tooling, and automation.

- Strong computer science fundamentals, with deep understanding of Linux OS principles, computer networks, storage systems, GPU systems, and databases, along with systematic troubleshooting and root-cause analysis skills.

- Familiar with core reliability practices, including monitoring and alerting, capacity management, change management, canary/gray releases, incident response, and postmortem processes.

- Strong communication and collaboration skills, with the ability to proactively identify problems, drive cross-team execution, and demonstrate strong ownership and results-oriented mindset.

- Hands-on experience operating public cloud platforms, or deep familiarity with major cloud providers such as OCI, AWS, Azure, GCP, etc, including understanding of their underlying mechanisms.

- Experience with large-scale cloud host delivery, image/AMI systems, resource scheduling, network adaptation, and virtualization technologies such as KVM/QEMU.

- Familiar with containers and cloud-native ecosystems, including Docker, Kubernetes, and containerd, with a solid understanding of isolation mechanisms like cgroups and namespaces.

- Experience maintaining GPU clusters, including drivers, CUDA, MIG, topology awareness, troubleshooting, stress testing, and GPU delivery pipelines.

- Proven experience in reliability-focused initiatives such as failure drill systems, capacity governance, change governance, observability platforms, and resource cost optimization.

- Open-source contributions, technical blogs, patents, or technical sharing experience are highly preferred.

- Experience operating large-scale production environments is a strong plus.