24 hours ago
Base Salary
$152k - $288k/yr
Responsibilities
- Design, develop, and operate distributed systems managing data, compute, and networking for large-scale AI workloads.
- Build software and automation to orchestrate workloads across thousands of GPUs and petabytes of storage in multi-region clusters.
- Translate AI/ML research requirements into scalable, high-performance infrastructure solutions.
- Improve system reliability, performance, and observability to meet exascale standards.
- Collaborate with security, networking, platform, AI research, and engineering teams on architecture and infrastructure evolution.
- Participate in design reviews and system architecture discussions.
Requirements
- Bachelor’s degree or equivalent experience in Computer Science, Computer Engineering, or a related technical field.
- 5+ years of experience developing and operating large-scale distributed systems, infrastructure platforms, or HPC environments.
- Strong programming skills in C++, Python, or Go, with experience designing production-quality software systems.
- Strong understanding of distributed systems, data management, and large-scale orchestration frameworks.
- Hands-on experience with high-performance storage such as Lustre, GPFS, or BeeGFS and orchestration or scheduling systems such as Slurm, Kubernetes, or LSF.
- Familiarity with Azure, AWS, GCP, and infrastructure automation tools.
- Strong problem-solving, ownership, communication, and cross-functional collaboration skills.
- Preferred qualifications include a graduate degree, exascale data management or scheduling expertise, AI/ML research infrastructure experience, distributed training experience with PyTorch, JAX, or NeMo, and leadership in architecture, performance optimization, or reliability engineering.
Benefits
- Eligible for equity and benefits.
- Base salary is provided in location- and experience-dependent ranges for Level 3 and Level 4.
- Applications will be accepted at least until October 18, 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.