As a Software Engineer in NVIDIA’s Internal Infrastructure Group, you’ll design and build distributed systems that power the workflows behind our next generation of GPUs and AI chips. The software you create will help thousands of engineers develop world-changing technology faster, more efficiently, and at scale. You’ll help scale the infrastructure that validates the world’s most advanced GPUs.
What you'll be doing:
Build and extend scalable, high-performance infrastructure services, platforms, and tools that improve reliability and developer productivity across NVIDIA’s chip-design ecosystem.
Design and optimize distributed workflows that orchestrate millions of regression and validation workloads across heterogeneous compute clusters.
Own systems end-to-end, from gathering requirements and proposing technical designs to implementation, performance analysis, testing, and deployment.
Collaborate with internal teams to understand workflows, identify bottlenecks, and deliver automation that accelerates engineering workflows.
Analyze and tune system performance across distributed services using profiling, tracing, and telemetry to help bring next-generation hardware and AI models to market faster.
This role focuses on building infrastructure software and distributed systems rather than operating production infrastructure
What we need to see:
BS or MS in Computer Science or a related field (or equivalent experience).
5+ years of professional software development experience.
Strong understanding of data structures, algorithms, concurrency, and system design.
Experience designing distributed systems that scale and taking ownership of those systems through implementation, evolution, and production support.
Proficiency in modern programming languages (Python, C++, Go, or similar) on Linux systems, with experience building large-scale services, infrastructure tooling, or distributed systems.
Ability to reason about trade-offs between performance, reliability, and maintainability.
Ways to stand out from the crowd:
Passion for improving engineering workflows and enabling others to move faster.
Hands-on familiarity with profiling, tracing, or performance-optimization techniques.
Understanding of chip-design, verification, or modern ML workflows.
NVIDIA is widely recognized as one of the most desirable employers in technology. We attract some of the world’s most forward-thinking and dedicated engineers. If you’re driven by curiosity, care deeply about performance and reliability, and love building systems that empower other developers, we want to meet you.
#LI-Hybrid
You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
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.Top Skills
What We Do
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, NVIDIA is increasingly known as “the AI computing company.”
