The NVIDIA Developer Tools Always-On Profiling (AON) team is building a low-overhead, production-ready GPU profiling service that scales across clusters and helps customers understand and optimize their AI workloads. We are looking for a Software Engineering Manager to lead this growing team, strengthen execution and engineering practices, and grow talent in a high-impact, multi-functional environment.
What you’ll be doing:
Translate product and business objectives into clear engineering roadmaps, achievements, and success criteria and guide the team to execution.
Create clarity on goals, scope, and priorities, and ensure the team delivers high-quality, maintainable software on a predictable cadence.
Lead a team of system software engineers building and evolving profiling services, data flows, and integrations across the NVIDIA stack and external ecosystems.
Collaborate with engineering teams, program and product management, and partners to align roadmaps, manage dependencies, and integrate AON into existing workflows and infrastructure.
Cultivate a culture of ownership, initiative, and mentorship where more engineers lead cross-cutting work and make sound technical decisions.
What we need to see:
BS or MS in Computer Science, Computer Engineering, or related field, or equivalent experience.
8+ overall years of professional software engineering experience and 3+ years of hands-on software engineering management experience leading large complex system software projects with a focus on functionality, security, performance, and stability.
Solid background in system software (e.g., operating systems, hardware-software interactions and performance analysis/optimizations, real-time systems) sufficient to evaluate designs, ask the right questions, and guide trade-offs for production services.
Strong C/C++ programming and debugging skills in Linux.
Proven ability to turn high-level goals into concrete plans, key results, and status reporting for complex software projects.
Experience introducing or improving engineering processes (planning, estimation, tracking, reviews) in a way that increases reliability and predictability without slowing teams down.
Proven experience in managing/leading software engineers: setting expectations, coaching, feedback, and growth support.
Demonstrated ability to develop a healthy team culture: psychological safety, inclusive collaboration, constructive debate, and shared ownership.
Outstanding written and verbal communication; can adapt messaging for engineers, cross-functional partners, and leadership, and clearly convey complex status/risks. Experience collaborating across boundaries and/or with external partners on shared work.
Ways to stand out from the crowd:
Composure in handling a diverse range of issues, making balanced decisions that carefully weigh technical limitations, user requirements, and business consequences.
Experience with profiling, tracing, observability, or performance analysis tools; or with services that must balance low overhead with rich visibility.
Track record helping an engineering team scale either in size or scope -- while improving execution quality, processes, and culture.
Examples of guiding teams through ambiguous problem spaces, clarifying direction, and iterating toward impactful outcomes in partnership with product and other partners.
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.”
