Senior Software Engineer, Capacity Management - DGX Cloud

Posted 19 Hours Ago
Be an Early Applicant
Santa Clara, CA, USA
In-Office
200K-322K Annually
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Design and build distributed services, data pipelines, APIs, and integrations for GPU capacity planning, reservations, allocation, forecasting, and utilization. Establish unified capacity models across cloud providers and regions, automate operational workflows, improve observability and reliability, and resolve complex production issues. Lead technical design reviews, set engineering standards, mentor engineers, and collaborate cross-functionally on business-critical DGX Cloud infrastructure.
Summary Generated by Built In

NVIDIA DGX Cloud provides the infrastructure and software platform that enables enterprises to build, train, and deploy AI at scale. As demand for accelerated computing grows, effective capacity management is essential to delivering reliable customer experiences while maximizing the utilization of constrained GPU infrastructure.
 

We are looking for a Senior Software Engineer to design and build the systems that connect customer demand, infrastructure supply, reservations, allocation, and utilization across DGX Cloud environments. You will work with engineering, product, operations, finance, and business teams to transform complex capacity data and operational processes into scalable software and automated decision-making.
 

What You’ll Be Doing:

  • 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 other 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.
     

What We Need to See:

  • BS or equivalent experience in Computer Science, Computer Engineering, or a related technical field.
  • 12+ years of software engineering experience building production systems.
  • Strong programming experience in languages such as Python, Go, Java, or similar.
  • 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.

Ways to Stand Out From the Crowd:

  • 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 running 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.
     

NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing, and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars. NVIDIA is looking for phenomenal people like you to help us accelerate the next wave of artificial intelligence. NVIDIA is broadly recognized as one of the technology world’s most desirable employers. We have some of the most forward-thinking and dedicated people in the world working for us.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 200,000 USD - 322,000 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until September 24, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Skills Required

  • Bachelor’s degree or equivalent experience in Computer Science, Computer Engineering, or a related technical field
  • 12+ 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 translate ambiguous business and operational requirements into technical designs
  • Strong communication skills and experience working across engineering and non-engineering organizations
  • 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 operating 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

NVIDIA Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.

  • Equity Value & Accessibility Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
  • Healthcare Strength Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
  • Retirement Support Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.

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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

What We Do

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”

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