Senior Software Engineer, Capacity Management - DGX Cloud

at Nvidia

USD 140,000-270,200 per year

SENIOR

✅ On-site

Tech Stack
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

AI @ 4 API @ 4 Communication @ 7 Data Modeling @ 7 Data Pipelines @ 4 Distributed Systems @ 4 GPU @ 4 Go @ 7 Java @ 7 Kubernetes @ 4 Machine Learning Observability @ 7 Python @ 7

Details

NVIDIA DGX Cloud provides the infrastructure and software platform that enables enterprises to build, train, and deploy AI at scale. This role focuses on building capacity-management systems that connect customer demand, infrastructure supply, reservations, allocation, and utilization across DGX Cloud environments.

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 currently dependent on manual analysis and coordination.
Build APIs, tools, and integrations that enable DGX Cloud systems and teams to make capacity-aware decisions.
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 the reliability, performance, and scalability of capacity-management services.

Requirements

Bachelor's degree or equivalent experience in Computer Science, Computer Engineering, or a related technical field.
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 working 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 Qualifications

Experience with GPU infrastructure, AI/ML platforms, schedulers, cluster management, or accelerated computing.
Experience building capacity planning, inventory, supply-and-demand, quota, reservation, or resource-allocation systems.
Familiarity with optimization, forecasting, simulation, or operations-research techniques.
Experience managing infrastructure across multiple cloud providers or geographically distributed environments.
Experience serving as a technical lead for cross-functional, business-critical initiatives.
Demonstrated success improving infrastructure utilization while maintaining reliability and customer commitments.

Benefits

Equity and benefits are provided.
NVIDIA is committed to fostering an inclusive work environment and is an equal opportunity employer.

Applications for this job will be accepted at least until September 15, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes.