Senior Software Engineer - Deep Learning Compiler CI Infrastructure
NVIDIA · California, United States
- Hybrid
- Full-time
- $180,000 / year
- California, United States
Job highlights
- Own and evolve CI/CD for deep learning compilers.
- Orchestrate ML workloads on GPU/accelerator environments.
- Improve CI reliability and reduce failures.
- Apply automation and AI to developer workflows.
- Build reusable and self-service CI platforms.
About the role
Senior Software Engineer Deep Learning Compiler CI Infrastructure at NVIDIA
NVIDIA's invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company”.
About the Role
In this role, you will work closely with deep learning compiler engineers to own and evolve the CI/CD infrastructure that powers the development lifecycle of NVIDIA's deep learning compiler stacks. Responsibilities include designing and operating scalable CI systems that orchestrate ML workloads across diverse GPU and accelerator environments, deliver reliable correctness and performance signals, and serve as a primary technical point of contact for CI health, new project onboarding, and new architecture bring-up.
What You'll Be Doing
- 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.
What We Need To See
- 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, GitHub Actions, 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.
- 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.
Ways To Stand Out From The Crowd
- Experience crafting and shipping sophisticated AI/agent-based systems that improve continuous integration or developer efficiency. These systems include intelligent test selection, automated triage and routing, regression localization, autonomous remediation, and developer-assist workflows.
- Experience operating CI for DL/GPU software environments, including multi-GPU / multi-node workloads on Slurm, Kubernetes, or cloud platforms.
- Familiarity with compiler IRs and infrastructure such as LLVM/MLIR, XLA/HLO, Triton IR, cuTile, or TileIR, especially in the context of testing, debugging, and validating compiler-driven workloads.
Compensation and Benefits
With competitive salaries and a generous benefits package, we are widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us and, due to unprecedented growth, our exclusive engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 140,000 USD - 224,250 USD.
You will also be eligible for equity and benefits.
Application Information
Applications for this job will be accepted at least until May 3, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
Equal Opportunity Employer Statement
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
Key skills/competency
- Senior Software Engineer
- Deep Learning
- Compiler CI Infrastructure
- CI/CD
- Python
- Distributed Systems
- AI/LLM
- GPU
- Kubernetes
- Software Engineering
Skills & topics
- Senior Software Engineer
- Deep Learning
- Compiler
- CI Infrastructure
- CI/CD
- Python
- Distributed Systems
- AI
- GPU
- Software Engineering
How to get hired
- Tailor your resume: Highlight experience in CI/CD, Python, distributed systems, and AI/LLM systems relevant to NVIDIA's deep learning compiler infrastructure.
- Showcase your portfolio: Provide links to projects demonstrating your ability to design, scale, and operate complex CI/CD platforms and AI/LLM systems.
- Prepare for technical interviews: Expect questions on distributed systems, Python coding, CI/CD best practices, and deep learning compiler concepts.
- Research NVIDIA's culture: Understand their focus on AI, GPU technology, and fostering innovation to align your answers with their values.
- Demonstrate impact: Quantify your achievements in improving developer efficiency, signal quality, or operational metrics in previous roles.
Technical preparation
Behavioral questions
Frequently asked questions
- What specific deep learning compiler technologies are used at NVIDIA for this Senior Software Engineer role?
- While the job description doesn't list all specific internal technologies, it mentions familiarity with compiler IRs and infrastructure such as LLVM/MLIR, XLA/HLO, Triton IR, cuTile, or TileIR is a plus. You'll be working on CI/CD infrastructure for NVIDIA's deep learning compiler stacks.
- What is the expected experience level for a Senior Software Engineer Deep Learning Compiler CI Infrastructure at NVIDIA?
- NVIDIA requires at least 5+ years of experience in designing, scaling, and operating CI/CD, build/release, or developer infrastructure for complex software systems. A BS, MS, or PhD in a related field is also expected, or equivalent experience.
- How does NVIDIA use AI in its recruiting process for this Senior Software Engineer position?
- NVIDIA explicitly states they use AI tools in their recruiting processes. This may involve AI assisting in resume screening, candidate matching, or interview analysis to identify the best-fit candidates for roles like the Senior Software Engineer.
- What programming languages are essential for the Senior Software Engineer Deep Learning Compiler CI Infrastructure role at NVIDIA?
- Python is a required skill for this role. Strong software engineering skills in Python are necessary to design, implement, and debug distributed systems end-to-end.
- What kind of impact can a Senior Software Engineer Deep Learning Compiler CI Infrastructure make at NVIDIA?
- You will significantly impact the development lifecycle of NVIDIA's deep learning compiler stacks by designing and operating scalable CI systems. Your work will improve reliability, speed up development, and ensure correctness and performance signals, directly contributing to the advancement of AI computing.
- Does NVIDIA offer remote work options for the Senior Software Engineer Deep Learning Compiler CI Infrastructure position?
- The job description does not explicitly state if this position is remote, hybrid, or on-site. Given the nature of infrastructure roles and NVIDIA's typical work arrangements, it is likely to be on-site or hybrid, but it's best to confirm during the application process.
- What are the key responsibilities for a Senior Software Engineer focusing on CI Infrastructure for Deep Learning Compilers at NVIDIA?
- Key responsibilities include building and improving CI infrastructure, enhancing CI reliability and signal quality, applying automation and AI to workflows, and developing self-service CI platforms in close collaboration with various engineering teams.