Manager, System Software Engineering - Infrastructure Engineering and Automation
NVIDIA Corporation (company site, opens in a new tab)10+ yrsPuneOn-siteDirect career pageEst. 40–65 LPA
Posted 13h ago
Reach people at NVIDIA Corporation
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at NVIDIA Corporation you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Lead and grow infrastructure and validation engineering teams responsible for CI/CD, test automation, lab operations, and hardware health to support NVIDIA’s Local AI and PC gaming R&D.
- Define and drive technical roadmap, priorities, and delivery for validating AI inference frameworks and gaming drivers on platforms including RTX and DGX systems.
- Collaborate across multiple teams to build scalable automation, debugging tools, and ensure reliable hardware labs to accelerate engineering productivity.
Minimum Requirements
- Bachelor's or Master's degree in Computer Engineering, Computer Science, Electrical Engineering, or related field, or equivalent experience.
- Minimum 3 years in management and over 10 years of relevant software engineering experience focused on system software, platform, runtime, or systems infrastructure development.
- Strong knowledge of system programming and operating systems concepts, including APIs, concurrency, resource management, and software-hardware interactions.
- Experience setting technical strategy, leading multi-team engineering programs, managing staffing, capacity, schedules, and communicating technical decisions to senior stakeholders.
Ideal Candidate Profile
- Experience with graphics software, GPU or device-driver stacks, DirectX, or Windows platform bring-up.
- Background in local AI inference frameworks (e.g., llama.cpp, PyTorch), CUDA or GPU programming preferred.
- Experience building or supporting system software, runtimes, developer tools, test frameworks, and performance analysis or telemetry tools in hardware-backed validation environments.