Senior Staff Site Reliability Engineer
NVIDIA · Posted Sep 23
Graphics processing units, artificial intelligence platforms, accelerated computing, and data center solutions
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About the role
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years, and today is tapping into the unlimited potential of AI to define the next era of computing. The team is seeking a Senior Staff Software Engineer to build the runtime foundation for NVIDIA's enterprise AI platforms, providing technical leadership for systems that deploy, operate, and scale AI applications, inference services, and databases across cloud and on-premises environments.
What you will do
- 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.
Skills used in this role
What the employer is looking for
- 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.
Preferred qualifications
- 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.
Benefits and support
- NVIDIA offers highly competitive salaries and a comprehensive benefits package.
- NVIDIA is committed to encouraging a diverse work environment and proud to be an equal opportunity employer.
- 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.
About NVIDIA
NVIDIA Corporation is a multinational technology company that designs graphics processing units (GPUs) for the gaming and professional markets, as well as system on a chip units (SoCs) for the mobile computing and automotive market. Pioneering accelerated computing, the company has become a driving engine of modern artificial intelligence, deep learning, and data center infrastructure.
- Industry
- Semiconductors
- Company size
- 42000+ employees
- Founded
- April 5, 1993
- Location
- Santa Clara, California, USA
- Funding stage
- Public Company
Funding
Public Company · $5M raised
Leadership
Founder, President and Chief Executive Officer
Executive Vice President and Chief Financial Officer
Founder and NVIDIA Fellow
Executive Vice President, Worldwide Field Operations
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