3 days ago
Base Salary
$168k - $270k/yr
Responsibilities
- Design and build automation frameworks, workflows, and data models for provisioning, patching, image deployment, telemetry, and change management at scale.
- Own the full lifecycle of services from architecture and development through deployment, operations, incident response, and continuous improvement.
- Develop software tools and platforms integrating data center systems, observability stacks, infrastructure control planes, and deployment pipelines.
- Monitor and operate large-scale GPU and Kubernetes production environments using Grafana, OpenTelemetry, and PagerDuty.
- Build predictive, automated break-fix, and self-remediation systems based on incident analysis.
- Participate in on-call rotations, incident response, blameless postmortems, and root-cause-focused reliability improvements.
- Scale systems through automation and self-service tools that improve reliability and engineering velocity.
Requirements
- At least 6 years of experience in SRE, production engineering, or infrastructure software engineering for large-scale, highly available environments.
- Bachelor’s degree in Computer Science, Engineering, Physics, Mathematics, or a related field, or equivalent experience.
- Strong production software development skills in Python and/or Go, including designing, building, and owning production-quality tools and services.
- Deep knowledge of Kubernetes, Linux systems administration, and/or container technologies, with experience operating bare-metal and cloud infrastructure.
- Experience building data center automation for OS provisioning, image deployment, patching, packaging, and configuration management.
- Experience with CI/CD tooling and infrastructure-as-code workflows.
- Strong understanding of observability practices, including metrics, logging, distributed tracing, and alerting design.
- Excellent communication skills and the ability to present technical work persuasively across multifunctional teams.
- Preferred experience delivering large-scale automation or reliability platforms, debugging and optimizing code, reducing system-level toil, and working with DCIM systems and asset database design.
Benefits
- Eligible for equity and benefits.
- Applications are accepted at least until October 31, 2026.
Tech Stack
Categories
DevOpsSite Reliability
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.