4 days ago
Base Salary
$184k - $357k/yr
Responsibilities
- Lead the overall architecture and design of a distributed storage service optimized for AI/ML.
- Develop and maintain robust, scalable Go programs deployed within open-source ecosystems including Kubernetes.
- Develop and maintain user-space applications, containers, Go bindings, and CLI tools.
- Build features that improve availability and reliability for large-scale distributed storage deployments.
- Collaborate with NVIDIA Research, Computing, Product, cross-functional teams, and external customers to deliver cloud services.
- Automate distributed storage service deployment, management, and monitoring end to end.
- Own product delivery from inception through support and lifecycle stages.
Requirements
- Bachelor of Science in Computer Science or a related field, or equivalent experience, with 8+ years of industry experience.
- Strong background developing distributed systems with Go, Kubernetes, and cloud service provider integrations.
- Proven track record delivering distributed services across varied distributed computing environments.
- Experience implementing storage services and interfaces for scalable, high-performance, and reliable solutions.
- Experience developing and maintaining enterprise software and deploying, managing, and debugging applications in Kubernetes.
- Strong communication and presentation skills.
- Preferred experience architecting, building, and deploying distributed services on large-scale, multi-petabyte to exabyte clusters with millions of users.
- Preferred experience with accelerated computing environments such as GPU Direct Storage, DPU, and RDMA.
Benefits
- Eligible for equity and benefits.
- Applications will be accepted at least until October 20, 2026.
- The base salary range varies by location, experience, and comparable employee pay; Level 4 is listed at $184,000-$287,500 and Level 5 at $224,000-$356,500.
Tech Stack
Categories
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.