ByteDance
Software Engineer, AI Infrastructure-Compute Efficiency
San Jose, California · Full-time · Posted Oct 28, 2026
- Experience
- 3+ years of relevant industry experience; Ph.D. degree and strong publication records can be an exception.
- Education
- B.S./M.S. degree in Computer Science, Computer Engineering or a related area; Ph.D. degree and strong publication records can be an exception.
About the job
Designs and optimizes large-scale Kubernetes infrastructure, resource scheduling, and container runtimes for diverse workloads, including AI and LLM applications.
What you'll do
- Evolve Kubernetes platform architecture and improve control- and data-plane performance, scalability, and resilience.
- Build observability and performance analysis frameworks, define system-level SLOs, and tune production systems.
- Develop unified resource management and scheduling systems, and optimize container runtime environments.
What they ask for
- B.S./M.S. degree in Computer Science, Computer Engineering, or a related area, with 3+ years of relevant industry experience; a Ph.D. degree and strong publication records can be an exception.
- Solid understanding of at least one of: Unix/Linux environments, distributed and parallel systems, high-performance networking systems, or developing large-scale software systems.
- Familiarity with Docker and Kubernetes.
- Proficiency in at least one of Python, Go, C++, Rust, or Java.
Nice to have
- Knowledge of big data or machine learning workflows in Kubernetes, or experience contributing to cloud-native open-source projects.
- Hands-on containerized-application project experience, or familiarity with Prometheus, Grafana, or distributed tracing systems.
Tools
Kubernetes, Docker, Python, Go, C++, Rust, Java, Prometheus
AI focus
Optimizes compute infrastructure and resource use for AI/LLM workloads; supports AI services and machine learning workflows.
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