ByteDance
Software Engineer, AI Infrastructure-Compute Efficiency
Seattle, Washington · 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 to improve performance, reliability, and resource efficiency for AI/LLM and other workloads.
What you'll do
- Design and evolve Kubernetes infrastructure platforms for performance, scalability, and resilience.
- Optimize Kubernetes control- and data-plane performance, pod lifecycle, orchestration, and system throughput.
- Build observability and performance-analysis frameworks, define system-level SLOs, and develop unified resource-management and scheduling systems.
What they ask for
- B.S./M.S. degree in Computer Science, Computer Engineering, or a related area; Ph.D. with strong publication records can be an exception.
- Solid understanding of at least one listed field: 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 with 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 use for AI/LLM workloads; supports AI/ML and LLM initiatives.
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