3 days ago
Base Salary
$184k - $357k/yr
Responsibilities
- Design services and own cloud infrastructure for physics-informed and data-driven scientific workflows.
- Design algorithms and improve system performance across application code, numerical solvers, distributed services, APIs, and heterogeneous CPU/GPU computing.
- Build, deploy, and operate scalable I/O infrastructure for checkpointing, data loading, and pre- and post-processing.
- Optimize compute, storage, and network architectures for physics- and simulation-driven applications.
- Debug processes, threads, deadlocks, synchronization, scheduling, IPC, memory management, file systems, and I/O.
- Collaborate with multiple teams independently and with minimal direction.
Requirements
- BS/MS degree in Computer Science or a related area, or equivalent experience.
- 10+ years of experience building and operating distributed, compute- and data-intensive cloud platform-as-a-service systems.
- Proficiency in a compiled language such as Go, Rust, or C++.
- Strong foundational knowledge of cloud computing, datacenter architecture, cloud security architecture, virtualization, resource pooling, and elasticity.
- Strong knowledge of distributed systems, parallel processing, fault tolerance, consensus, parallel algorithms, shared and distributed memory architectures, and message passing.
- Hands-on debugging and algorithmic system-design skills, including experience with large-scale loosely coupled distributed systems.
- Self-motivation, strong interpersonal skills, and the ability to work independently across multiple teams.
- Preferred: experience building, deploying, and operating AI platforms on HPC clusters and cloud-native systems involving distributed storage, scheduling, and orchestration.
- Preferred: experience configuring and troubleshooting hardware, operating systems, kernels, and compilers for performance.
- Preferred: experience debugging and optimizing compute, networking, and I/O frameworks and customizing third-party source code.
Benefits
- Eligible for equity and benefits.
- Base salary varies by location, experience, and comparable employee pay; the posting lists Level 4 and Level 5 salary ranges.
- Applications are accepted at least until October 21, 2026.
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.