1 day ago
Base Salary
$140k - $270k/yr
Responsibilities
- Design and build distributed services and data pipelines for capacity planning, allocation, reservations, and utilization.
- Develop a unified model of available, committed, and forecasted GPU capacity across cloud providers, regions, clusters, and products.
- Automate capacity-management workflows that currently depend on manual analysis and coordination.
- Build APIs, tools, and integrations that enable capacity-aware decisions across DGX Cloud systems and teams.
- Improve forecasting, scenario planning, and operational visibility by combining demand signals with infrastructure supply data.
- Establish monitoring, data-quality controls, and service-level indicators for capacity systems.
- Lead technical design reviews, establish engineering standards, and mentor other engineers.
- Diagnose complex production issues and improve service reliability, performance, and scalability.
Requirements
- BS in Computer Science, Computer Engineering, or a related technical field, or equivalent experience.
- 5+ years of software engineering experience building production systems.
- Strong programming experience in Python, Go, Java, or similar languages.
- Experience designing distributed systems, backend services, APIs, and data-processing pipelines.
- Experience with cloud infrastructure, Kubernetes, compute platforms, or large-scale resource-management systems.
- Strong understanding of data modeling, system integration, observability, and production operations.
- Ability to turn ambiguous business and operational requirements into clear technical designs.
- Strong communication skills and experience working across engineering and non-engineering organizations.
- Preferred experience with GPU infrastructure, AI/ML platforms, schedulers, cluster management, or accelerated computing.
- Preferred experience building capacity planning, inventory, supply-and-demand, quota, reservation, or resource-allocation systems.
- Familiarity with optimization, forecasting, simulation, or operations-research techniques is preferred.
- Preferred experience managing infrastructure across multiple cloud providers or geographically distributed environments and serving as a technical lead for cross-functional, business-critical initiatives.
- Demonstrated success improving infrastructure utilization while maintaining reliability and customer commitments is preferred.
Benefits
- Eligible for equity and benefits.
- Applications will be accepted at least until September 15, 2026.
- This posting is for an existing vacancy.
Tech Stack
Categories
BackendData Engineering
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.