Senior Software Engineer - NIM Factory Container and Cloud Infrastructure

NVIDIA is the platform upon which every new AI-powered application is built. We are seeking a Senior Software Engineer focused on container and cloud infrastructure. You will help design and implement our core container strategy for NVIDIA Inference Microservices (NIMs) and our hosted services. You will build enterprise-grade software and tooling for container build, packaging, and deployment. You will help improve reliability, performance, and scale across thousands of GPUs. There is much more to build ahead, including support for disaggregated LLM inference and other emerging deployment patterns.What you'll be doing:Design, build, and harden containers for NIM runtimes, inference backends; enable reproducible, multi-arch, CUDA-optimized builds.Develop Python tooling and services for build orchestration, CI/CD integrations, Helm/Operator automation, and test harnesses; enforce quality with typing, linting, and unit/integration tests.Help design and evolve Kubernetes deployment patterns for NIMs, including GPU scheduling, autoscaling, and multi-cluster rollouts.Optimize container performance: layer layout, startup time, build caching, runtime memory/IO, network, and GPU utilization; instrument with metrics and tracing.Evolve the base image strategy, dependency management, and artifact/registry topology.Collaborate across research, backend, SRE, and product teams to ensure day-0 availability of new models.Mentor teammates; set high engineering standards for container quality, security, and operability.What we need to see:A degree in Computer Science, Computer Engineering, or a related field (BS or MS) or equivalent experience.6+ years building production software with a strong focus on containers and Kubernetes.Strong Python skills building production-grade tooling/servicesExperience with Python SDKs and clients for Kubernetes and cloud servicesExpert knowledge of Docker/BuildKit, containerd/OCI, image layering, multi-stage builds, and registry workflows.Deep experience operating workloads on Kubernetes.Hands-on experience building and running GPU workloads in k8s, including NVIDIA device plugin, MIG, CUDA drivers/runtime, and resource isolation.Excellent collaboration and communication skills; ability to influence cross-functional design.Ways to stand out from the crowd:Expertise with Helm chart design systems, Operators, and platform APIs serving many teams.Experience with OpenAI API, Hugging Face API as well as understanding difference inference backends (vLLM, SGLang, TRT-LLM)Background in benchmarking and optimizing inference container performance and startup latency at scale.Prior experience designing multi-tenant, multi-cluster, or edge/air-gapped container delivery.Contributions to open-source container, k8s, or GPU ecosystems.With competitive salaries and a generous benefits package, we are widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us and, due to unprecedented growth, our exclusive engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you!Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 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 April 13, 2026.This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes.NVIDIA is committed to fostering 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.SummaryLocation: US, CA, Santa Clara; US, CA, RemoteType: Full time