Senior Software Engineer: Capacity & Resource Orchestration

NVIDIA Corporation; Santa Clara (CA); On-site; USD 140,000 - 224,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA is seeking a Senior Software Engineer to design and build capacity-management systems for DGX Cloud, connecting demand, infrastructure, reservations, and utilization across environments.

You will work with engineering, product, operations, and finance teams to transform capacity data and processes into scalable software and automated decisions, while improving forecasting and visibility across GPU resources.

Qualifications

• BS or equivalent in Computer Science, Computer Engineering, or related field.
• 5+ years of software engineering experience building production systems.
• Strong programming experience in Python, Go, Java, or similar.

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.
• Build APIs, tools, and integrations that enable other DGX Cloud systems to make capacity-aware decisions.
• Improve forecasting, scenario planning, and operational visibility by combining demand signals with data.

Skills

BS in CS

5+ years experience

Python/Go/Java

Distributed systems

Cloud/Kubernetes

Data modeling

Observability

Cross-functional communication

Education

BS or equivalent in CS/CE

Tools

Kubernetes

Cloud platforms

Job description

NVIDIA is seeking a Senior Software Engineer to design and build capacity-management systems for DGX Cloud, connecting demand, infrastructure, reservations, and utilization across environments.

You will work with engineering, product, operations, and finance teams to transform capacity data and processes into scalable software and automated decisions, while improving forecasting and visibility across GPU resources.