Senior Software Engineer - NIM Factory Container and Cloud Infrastructure

at Nvidia
📍 Santa Clara, United States
USD 184,000-356,500 per year
SENIOR
✅ On-site

SCRAPED

Used Tools & Technologies

Not specified

Required Skills & Competences ?

Security @ 4 Docker @ 4 Kubernetes @ 4 Python @ 4 CI/CD @ 4 Communication @ 6 Helm @ 4 SRE @ 4 Microservices @ 4 API @ 4 LLM @ 4 CUDA @ 4 GPU @ 4

Details

NVIDIA is the platform upon which every new AI-powered application is built. This role is focused on container and cloud infrastructure for NVIDIA Inference Microservices (NIMs) and hosted services. You will design and implement core container strategy, build enterprise-grade software and tooling for container build, packaging, and deployment, and improve reliability, performance, and scale across thousands of GPUs. Work includes support for disaggregated LLM inference and other emerging deployment patterns.

Responsibilities

  • Design, build, and harden containers for NIM runtimes and 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.

Requirements

  • 10+ years building production software with a strong focus on containers and Kubernetes.
  • Strong Python skills building production-grade tooling/services.
  • Experience with Python SDKs and clients for Kubernetes and cloud services.
  • Expert knowledge of Docker/BuildKit, containerd/OCI, image layering, multi-stage and multi-arch builds, and registry workflows.
  • Deep experience operating workloads on Kubernetes, including GPU scheduling and autoscaling.
  • Strong understanding of LLM inference features, including structured output, KV-cache, and LoRa adapter.
  • Hands-on experience building and running GPU workloads in Kubernetes, including NVIDIA device plugin, MIG, CUDA drivers/runtime, and resource isolation.
  • Experience with instrumentation (metrics and tracing) and test automation (unit/integration tests).
  • Excellent collaboration and communication skills; ability to influence cross-functional design.
  • A degree in Computer Science, Computer Engineering, or a related field (BS or MS) or equivalent experience.

Ways to stand out

  • Expertise with Helm chart design systems, Operators, and platform APIs serving many teams.
  • Experience with OpenAI API, Hugging Face API and understanding different 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, Kubernetes, or GPU ecosystems.

Compensation & Benefits

  • Base salary ranges (depending on level and location):
    • Level 4: 184,000 USD - 287,500 USD
    • Level 5: 224,000 USD - 356,500 USD
  • You will also be eligible for equity and benefits (link provided in the original posting).

Equal opportunity & Application

  • Applications for this job will be accepted at least until September 22, 2025.
  • NVIDIA is an equal opportunity employer and is committed to fostering a diverse work environment.

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