- BS, MS, or PhD in Computer Science, Electrical Engineering, or a related field (or equivalent experience).
- 10+ overall years of software engineering experience, including 4+ years in an engineering management role leading teams of 10 or more engineers delivering production services at scale.
- Deep technical background in distributed storage systems, object storage platforms, or large-scale cloud data services; hands-on development experience in Go, C++, Python, or equivalent systems languages.
- Direct, hands-on experience building or scaling S3-compatible object storage systems in a production cloud or private cloud environment — with demonstrable improvements in throughput, durability, or operational efficiency.
- Demonstrated experience building or operating cloud storage services — with accountability for reliability, performance, and capacity at scale in a production environment.
- Proven track record of shipping production software on time — managing scope, risk, and delivery across multiple concurrent workstreams.
- Strong experience with modern software development and service delivery practices: CI/CD, automated testing, SLO-based reliability, production observability, and incident management.
- Demonstrated ability to attract, develop, and retain strong engineering talent in a driven environment, with a track record of growing engineers into senior and staff-level roles.
- Excellent written and verbal communication — able to translate complex technical trade-offs for product partners and engineering constraints for executive audiences.
Ways to Stand Out from the crowd
- Prior experience designing and operating internal cloud storage services (IaaS/PaaS) with well-defined SLAs, metered usage, and internal customer-facing APIs.
- Background in effective observability and system reliability engineering of distributed systems.
- Familiarity with AI infrastructure storage patterns: checkpoint storage, dataset versioning, write-once-read-many (WORM) access patterns, or storage-aware scheduling at 10k+ GPU scale. Experience managing capacity planning, cost optimization, and chargeback modeling for shared internal storage infrastructure.
- Track record of adopting AI-assisted development tools to meaningfully improve team productivity, with concrete examples. History of growing engineers into senior ICs or leads, and building diverse, inclusive teams with strong retention.
NVIDIA's Object Storage Platform and data movement tooling form a critical layer in keeping NVIDIA's GPU fleet productive — every model trained, every checkpoint saved, and every dataset staged passes through the systems this team builds and operates. This is a high-impact role at the center of NVIDIA's AI infrastructure.
We need passionate, hard-working and creative people to help us take on more of these unique opportunities in deep learning cloud solutions. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hard-working people in the world working for us. Are you creative and autonomous? Do you love a challenge? If so, we want to hear from you.
Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary range for this position is 272,000 USD – 431,250 USD.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until November 8, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.