ByteDance
Senior Software Engineer, AI Infrastructure-Compute Efficiency
Seattle, Washington · Senior · Full-time · Posted Oct 28, 2026
- Experience
- 3+ years of relevant industry experience; a 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 with strong publication records can be an exception.
About the job
Designs and optimizes large-scale Kubernetes infrastructure and resource scheduling to improve performance, reliability, and compute efficiency for diverse workloads, including AI and LLM applications.
What you'll do
- Evolve Kubernetes platform architecture and optimize control-plane and data-plane performance, pod lifecycle, and system throughput.
- Build observability and performance-analysis frameworks, define system-level SLOs, and tune production systems.
- Develop unified resource management and scheduling systems and optimize container runtimes for efficiency and reliability.
What they ask for
- B.S./M.S. degree in Computer Science, Computer Engineering, or a related area; a Ph.D. with 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 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.
- Familiarity with Prometheus, Grafana, or distributed tracing systems.
Tools
Kubernetes, Docker, Python, Go, C++, Rust, Java, Prometheus
AI focus
Optimizes compute infrastructure and resource scheduling for AI and LLM workloads.
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