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. This role focuses on building new infrastructure systems and distributed workflow platforms. What you'll be doing: Build and extend scalable, high-performance core infrastructure systems and workflow platforms that improve reliability and developer productivity across NVIDIA’s chip-design ecosystem. Design and optimize distributed systems that orchestrate millions of regression and validation workloads across heterogeneous compute environments. Design systems that coordinate dependency-aware execution across large-scale compute clusters. Define system architecture including APIs, data models, execution models, and scaling strategies. 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. What we need to see: BS or MS in Computer Science or a related field (or equivalent experience). 9+ years of professional software development experience. Strong foundation in data structures, algorithms, concurrency, and distributed system design. Demonstrated experience designing and building distributed systems from first principles — including defining APIs, data models, execution flows, and scaling approaches. Experience owning systems through design, implementation, and evolution — including handling trade-offs, failure modes, and system limitations. Experience working on systems involving scheduling, dependency resolution, or large-scale job orchestration. Proficiency in modern programming languages (Python, C++, Go, or similar) on Linux systems, with experience building large-scale systems or infrastructure software. Ability to clearly articulate architecture decisions, trade-offs, and how systems evolved over time. Ways to stand out from the crowd: Experience improving developer productivity through infrastructure or platform design. 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