Define and instrument SLIs and SLOs for inference and control plane services, including availability and latency, use error budgets to guide reliability improvements, and make production health visible to partner teams.
Participate in on-call and incident response, troubleshoot failures across routing, model runtimes, software, and infrastructure, and turn recurring issues into automation and durable fixes.
Collaborate with model, platform, storage, networking, security, and GPU infrastructure teams to design and operate services safely at scale.
What we need to see
8+ years of experience building or operating production services and large-scale distributed systems, including hands-on automation.
Strong programming skills in Python, Go, or a comparable language, with experience developing tools for production operations.
Experience with infrastructure as code, configuration management, or GitOps, and with building automation for repeatable service deployments and changes.
Strong knowledge of Linux, Kubernetes, containers, cloud infrastructure, distributed systems, and networking fundamentals; ability to diagnose failures in production.
Understanding of SRE principles, including SLIs, SLOs, error budgets, incident response, and reducing operational toil.
Experience instrumenting services and using metrics, logs, and traces to understand system behavior and improve reliability.
Clear technical communication and ability to work across engineering teams.
BS/MS in Computer Science or equivalent experience.
Ways to stand out from the crowd
Familiarity with technologies such as vLLM, SGLang, PyTorch, TensorRT-LLM, NVIDIA Dynamo, CUDA, or NCCL, and with GPU performance analysis.
Experience building Kubernetes operators, controllers, workload orchestration services, fleet management systems, or self-healing automation.
Experience with Terraform, Argo CD, CI/CD, policy validation, or safe deployment and rollback systems.
Experience developing with AI tools and agents.
Background with production AI inference or agentic workloads, including debugging issues across models, runtimes, Kubernetes, and hardware.
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. We have some of the most forward-thinking and hard-working people on the planet working for us. If you're creative, hard-working and self-motivated, we want to hear from you!
- Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are:
- 184,000 USD – 287,500 USD for Level 4; and 224,000 USD – 356,500 USD for Level 5.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until November 3, 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.
