← All roles

Deep Learning Compiler CI and Infrastructure Engineer

NVIDIA· Engineer, SW
Apply on company site
Shanghaifull-timePosted 3mo ago

About the role

Role focused on owning and evolving CI/CD infrastructure for NVIDIA's deep learning compiler stacks, delivering scalable CI systems across GPU and accelerator environments, and serving as the primary technical contact for CI health, onboarding, and architecture bring-up.

Responsibilities

  • Build, maintain, and improve CI infrastructure that supports development, verification, and release of NVIDIA’s deep learning compiler stacks across GPU and accelerator environments
  • Improve CI reliability and signal quality by reducing flakes, improving reproducibility, strengthening diagnostics, and making correctness and performance failures easier to understand and act on
  • Apply automation, AI, and agent-based workflows to reduce manual CI operations, speed up failure triage, and improve developer efficiency
  • Build reusable and self-service CI platforms that support multiple products, projects, model suites, hardware targets, and software configurations while partnering closely with compiler, infrastructure, and release teams

Qualifications

  • BS, MS, or PhD (or equivalent experience) in Computer Science, Computer/Electrical Engineering, Mathematics, or a related field
  • 5+ years of experience designing, scaling, and operating CI/CD, build/release, or developer infrastructure for complex software systems
  • Proven experience building CI platforms end-to-end using systems such as GitLab CI, Jenkins, or similar tools, including pipeline orchestration, compute/runner management, artifact and package systems, and observability, with strong emphasis on reliability, reproducibility, and debuggability
  • Strong software engineering skills (Python required), with the ability to design, implement, and debug distributed systems end-to-end
  • Familiarity with edge devices (SOC, e.g. NVIDIA Tegra) in host-target architecture, ability to debug it and knowledge of its automation nuances
  • Proven track record of designing, building, and deploying AI/LLM-based systems in real engineering workflows, demonstrating skill in evaluating trade-offs, failure modes, maintainability, and measurable impact on developer productivity, signal quality, or operational efficiency

Skills

Required:PythonCI/CD platform designDistributed systemsEdge devices debugging

Benefits

  • Competitive salaries
  • Generous benefits package
Last updated Oct 23, 2026. Interested? Apply on the company site.

About NVIDIA

World Leader in AI Computing

NVIDIA invents the GPU and drives advances in AI, HPC, gaming, creative design, autonomous vehicles, and robotics.

AIautonomous vehiclesgaminggpugraphics cardhigh performance computingliquid-ai-recruiting-targetllm
Company profileWebsite

More open roles at NVIDIA