Deep Learning Compiler CI and Infrastructure Engineer
Salary not listed • China, Shenzhen • Full-time
Posted 1d ago
Remote Work Policy
On-site
Employment Type
Full-time
Categories
AI Infrastructure Engineer
About the job
NVIDIA is seeking a Deep Learning Compiler CI and Infrastructure Engineer to join their team in Shenzhen, China. In this role, you will collaborate with deep learning compiler engineers to manage and enhance the CI/CD infrastructure that supports the development lifecycle of NVIDIA's deep learning compiler stacks. You will be responsible for designing and operating scalable CI systems that orchestrate ML workloads across various GPU and accelerator environments, ensuring reliable correctness and performance signals. This position serves as a primary technical contact for CI health, onboarding new projects, and integrating new architectures.
Responsibilities
- Build, maintain, and improve CI infrastructure for deep learning compiler stacks across GPU and accelerator environments.
- Enhance CI reliability and signal quality by reducing flakes, improving reproducibility, and strengthening diagnostics.
- Apply automation, AI, and agent-based workflows to reduce manual CI operations and speed up failure triage.
- Develop reusable, self-service CI platforms supporting multiple products, projects, and hardware targets.
- Serve as a technical point of contact for CI health, new project onboarding, and new architecture integration.
Requirements
- BS, MS, or PhD (or equivalent experience) in Computer Science, Computer/Electrical Engineering, Mathematics, or a related field.
- 5+ years of experience in designing, scaling, and operating CI/CD, build/release, or developer infrastructure for complex software systems.
- Proven experience building CI platforms end-to-end using tools like GitLab CI or Jenkins, including pipeline orchestration, compute management, artifact systems, and observability.
- Strong software engineering skills in Python, with experience in designing and debugging distributed systems.
- Familiarity with edge devices (SOC) in host-target architecture and their automation nuances.
- Track record of designing, building, and deploying AI/LLM-based systems in real engineering workflows.
Benefits
- Competitive salaries
- Generous benefits package