[Remote] Senior System Software Engineer - DevOps and Infrastructure Automation

Note: The job is a remote job and is open to candidates in USA. NVIDIA is a leading technology company revolutionizing computer graphics, PC gaming, and accelerated computing. As a Senior System Software Engineer on NVIDIA's AI Inference Operations Team, you will focus on DevOps and Infrastructure Automation, working to design and manage the infrastructure that powers AI inference products.ResponsibilitiesDesign, build, and operate the infrastructure backbone powering AI inference products — reliable, performant, and scalable at every layer!Own Kubernetes deployments end-to-end across cloud and on-prem: runbooks, canary checks, post-deploy validation, and rollbacks when neededArchitect CI/CD pipelines for automated build, test, packaging, and release of inference libraries and their container-based software stacksBuild observability that actually tells the truth about platform health — dashboards, logs, metrics, automated checks — and lead first-level incident triage with clean, actionable handoffs to engineeringManage cloud and on-prem environments with infrastructure-as-code (Terraform, Ansible, Helm, Crossplane), and chip away at toil using GitHub Actions, GitLab CI, and custom toolingOwn the security posture for infrastructure components: vulnerability scans, CVE remediation, and compliance with internal policiesCollaborate closely with deep learning framework engineers, compiler teams, and platform architects to streamline end-to-end deployment!SkillsBS/MS in CS/CE or equivalent experience, plus 7+ years operating production distributed systems (SRE / DevOps / Platform Ops)Deep Kubernetes expertise — components, subsystems, on-prem setup, and hands-on debugging of telemetry-heavy microservices across AWS, Azure, GCP, and on-premStrong CI/CD chops (GitLab CI, GitHub Actions), Git-based workflows, Linux systems programming, and scripting in Python and BashIaC fluency (Terraform, Ansible, Helm, Crossplane) and containerization depth (Docker, containerd, OCI)Proven reliability ownership — SLOs/SLIs, on-call, incident response, and post-incident reviews that drive measurable improvements — backed by hands-on experience with observability stacks like Prometheus, Grafana, and LokiA clear communicator who writes runbooks people actually use!MLOps experience — crafting, deploying, and operating machine learning pipelines end to endExperience in open-source development workflows and community engagement on projects like Triton Inference Server or ONNX RuntimeFamiliarity with GPU software stacks — CUDA, cuDNN, TensorRT, and inference serving frameworksExperience building custom test automation frameworks and using data-driven metrics to improve platform health and developer efficiencyDemonstrated ability to debug complex issues spanning kernel modules, container runtimes, and distributed networkingBenefitsYou will also be eligible for equity and [benefits](https://www.nvidia.com/en-us/benefits/).Company OverviewNVIDIA is a computing platform company operating at the intersection of graphics, HPC, and AI. It was founded in 1993, and is headquartered in Santa Clara, California, USA, with a workforce of 10001+ employees. Its website is https://www.nvidia.com.Company H1B SponsorshipNVIDIA has a track record of offering H1B sponsorships, with 448 in 2026, 1872 in 2025, 1354 in 2024, 976 in 2023, 835 in 2022, 601 in 2021, 529 in 2020. Please note that this does not guarantee sponsorship for this specific role.