Backend Software Engineer Graduate (Foundational Technology) - 2027 Start

About ByteDance

Our team is responsible for building ByteDance's cloud-native infrastructure, which powers all of the company's products.

We specialize in cutting-edge technologies in areas such as Kubernetes cluster management, runtime resource optimization, multi-cloud and multi-cluster solutions, and cloud-native infrastructure stability.

The team has released open-source projects such as Kubebrain and Katalyst, and we are focused on groundbreaking research and development of core technologies around resource pooling and elasticity.

We are looking for talented individuals to join our team.

As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth.

Responsibilities

• Build and Optimize Large-Scale Kubernetes Clusters;
• Design and evolve system architectures for ultra-large-scale Kubernetes clusters,
• Continuously improve the performance and stability of control systems in scenarios like big data and machine learning.
• Define and Enhance Kubernetes SLOs;
• Establish and optimize Service Level Objectives (SLOs) for Kubernetes clusters,
• Analyze end-to-end latency, identify performance bottlenecks, propose solutions, and implement them in production environments.
• Develop Observability for Kubernetes Clusters;
• Build and enhance observability systems to improve issue diagnosis efficiency,
• Create observability data warehouses and use data-driven approaches to optimize cluster performance.

Requirements

• Successful candidates must be able to commit to an onboarding date by the end of the year.
• Please state your availability and graduation date clearly in your resume.
• Individuals who are completing or have recently completed a Bachelor's degree in Software Development, Computer Science, Computer Engineering, or a related discipline.

Preferred

• Experience in developing or contributing to cloud-native open-source projects.
• Hands-on project experience with containerized applications through internships, coursework, or personal projects.
• Familiarity with observability tools and frameworks like Prometheus, Grafana, or distributed tracing systems.
• Knowledge of big data or machine learning workflows in a Kubernetes environment.

How to apply

• Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply.
• The application limit is applicable to our Company and its affiliates' jobs globally.
• Applications will be reviewed on a rolling basis - we encourage you to apply early.

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Questions

If you have any questions, please reach out to us at