Senior Software Engineer - NIM Factory Container and Cloud Infrastructure
at Nvidia
USD 184,000-356,500 per year
SCRAPED
Used Tools & Technologies
Not specified
Required Skills & Competences ?
Security @ 4 Docker @ 4 Kubernetes @ 4 Python @ 4 CI/CD @ 4 Hiring @ 4 Communication @ 6 Helm @ 4 SRE @ 4 Microservices @ 4 API @ 4 LLM @ 4 CUDA @ 4 GPU @ 4Details
NVIDIA is hiring a Senior Software Engineer to focus on container and cloud infrastructure for NVIDIA Inference Microservices (NIMs) and hosted services. The role involves designing and implementing a core container strategy, building enterprise-grade tooling for container build/packaging/deployment, and improving reliability, performance, and scale across thousands of GPUs. The team will work on supporting emerging deployment patterns such as disaggregated LLM inference.
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 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 and set high engineering standards for container quality, security, and operability.
Requirements
- BS/MS in Computer Science, Computer Engineering, or related field, or equivalent experience.
- 6+ years building production software with a strong focus on containers and Kubernetes.
- Strong Python skills building production-grade tooling and services.
- Experience with Python SDKs/clients for Kubernetes and cloud services.
- Expert 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 Kubernetes, including NVIDIA device plugin, MIG, CUDA drivers/runtime, and resource isolation.
- Excellent collaboration and communication skills; ability to influence cross-functional design decisions.
Ways to stand out
- Expertise with Helm chart design systems, Operators, and platform APIs serving many teams.
- Experience with OpenAI API and Hugging Face API; understanding differences between 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.
Benefits & Compensation
- Competitive salary and a generous benefits package; eligible for equity and NVIDIA benefits.
- Base salary ranges by level:
- Level 4: 184,000 USD - 287,500 USD
- Level 5: 224,000 USD - 356,500 USD
Applications accepted at least until September 14, 2025. NVIDIA is an equal opportunity employer committed to diversity and inclusion.