Software Engineer Graduate (Cloud Native Infrastructure) - 2026 Start (PhD)

About the role

The Compute Infrastructure team at ByteDance uses Kubernetes and Serverless technologies to build a large, reliable, and efficient compute infrastructure. This infrastructure powers hundreds of large-scale clusters globally, with over millions of online containers and offline jobs daily, including AI and LLM workloads. The team is dedicated to building cutting-edge, industry-leading infrastructure that empowers AI innovation, ensuring high performance, scalability, and reliability to support the most demanding AI/LLM workloads. The team is also dedicated to open-sourcing key infrastructure technologies, including projects in the K8s portfolio such as kubewharf (KubeBrain, Katalyst, Godel, etc.).

Responsibilities

• Assist in analyzing and supporting enhancements to Hyper-Scale AI Infrastructure platforms, focusing on improving performance, scalability, and resilience for both traditional workloads and large language model (LLM) applications.
• Contribute to performance optimization efforts for Kubernetes-based infrastructure, including monitoring pod lifecycle, tracking resource utilization, and analyzing system behavior under varying load conditions—working closely with senior engineers to identify improvement opportunities.
• Lead small-scale development tasks related to resource management and scheduling in Kubernetes clusters, such as testing configuration updates, automating routine resource allocation workflows, or contributing to tooling for efficiency tracking.
• Engage actively in team discussions on AI infrastructure design and optimization strategies, leveraging academic knowledge and personal projects to propose fresh insights and potential solutions.
• Develop and maintain clear technical documentation, including runbooks, architecture diagrams, and process guides, to strengthen knowledge sharing and operational efficiency across the team.

Qualifications

• Minimum Qualifications: Individuals who are completing or have recently completed a PhD degree in Software Development, Computer Science, Computer Engineering, or a related technical discipline. Proficiency in at least one major programming language such as Python, Go, C++, Rust, and Java. Solid understanding of at least one of the following fields: Unix/Linux environments, distributed and parallel systems, high-performance networking systems, developing large scale software systems.
• PREFERRED QUALIFICATIONS: Hands-on project experience with container and orchestration technologies such as Docker and Kubernetes through internships, coursework, or personal projects. Experience in developing or contributing to cloud-native open-source projects.