NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. Doing what’s never been done before takes vision, innovation, and talented people. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work.
We are seeking a Senior Staff Software Engineer to build the runtime foundation for NVIDIA’s enterprise AI platforms. You will provide technical leadership for systems that deploy, operate, and scale AI applications, inference services, and databases across cloud and on-premises environments.
What you'll be doing:
Define the architecture and technical roadmap for a scalable enterprise AI runtime platform.
Design Kubernetes-based systems for deploying, running, and scaling AI applications, inference services, and databases.
Build control-plane services, APIs, operators, and automation for workload provisioning, configuration, upgrades, and recovery.
Develop runtime capabilities for GPU scheduling, autoscaling, load balancing, and rate limiting.
Improve the performance, availability, and developer experience of large-scale AI inference services.
Build and automate relational and vector database services, including provisioning, scaling, backup, and failover.
Establish secure and consistent application lifecycle-management patterns spanning cloud-based and on-premises platforms.
Develop observability tools for monitoring, profiling, and debugging applications, GPU resources, inference workloads, and databases.
Lead technical initiatives across multiple functions, mentor engineers, and establish standards for the platform’s long-term evolution.
What we need to see:
BS, MS, or PhD in Computer Science, Engineering, or a related field—or equivalent experience.
8+ years of software engineering experience building distributed systems, cloud infrastructure, database platforms, or large-scale backend services.
Strong programming skills in Python, Go, C++, or Java, with experience delivering production-grade systems.
Proven track record designing scalable and highly available Kubernetes-based platforms and leading technical strategy, influence across teams, and tackle complex platform problems.
Experience building control planes, platform APIs, Kubernetes operators, or workload lifecycle-management systems.
Experience developing high-performance services for AI inference or other low-latency workloads.
Practical knowledge of relational or vector databases, including availability, replication, query optimization, and performance tuning.
Experience with GitOps, CI/CD, observability, and cloud-native security practices.
Ways to stand out from the crowd:
Experience building self-service platforms for application and infrastructure lifecycle management.
Experience with inference-serving frameworks, GPU-aware scheduling, or model-performance optimization.
Expertise in vector databases, GPU-accelerated query engines, or distributed data platforms.
Experience supporting the complete AI application lifecycle, from development through production serving and monitoring.
Contributions to open-source projects in Kubernetes, AI/ML infrastructure, databases, distributed systems, or observability.
NVIDIA is committed to encouraging a diverse 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.
Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/
Skills Required
- BS, MS, or PhD in Computer Science, Engineering, or a related field, or equivalent experience
- 8+ years of software engineering experience building distributed systems, cloud infrastructure, database platforms, or large-scale backend services
- Strong programming skills in Python, Go, C++, or Java, with production-grade systems experience
- Experience designing scalable and highly available Kubernetes-based platforms
- Experience leading technical strategy and influencing across teams
- Experience building control planes, platform APIs, Kubernetes operators, or workload lifecycle-management systems
- Experience developing high-performance services for AI inference or other low-latency workloads
- Practical knowledge of relational or vector databases, including availability, replication, query optimization, and performance tuning
- Experience with GitOps, CI/CD, observability, and cloud-native security practices
- Experience building self-service application and infrastructure lifecycle-management platforms
- Experience with inference-serving frameworks, GPU-aware scheduling, or model-performance optimization
- Expertise in vector databases, GPU-accelerated query engines, or distributed data platforms
- Experience supporting the complete AI application lifecycle from development through production serving and monitoring
- Open-source contributions in Kubernetes, AI/ML infrastructure, databases, distributed systems, or observability
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.
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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.
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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.
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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.
NVIDIA Insights
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.”
