NVIDIA is seeking a Senior Software Engineer to help design and implement core container strategy for NVIDIA Inference Microservices (NIMs) and hosted services, improving reliability, performance, and scale across thousands of GPUs
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 builds, and registry workflows
- Deep experience operating workloads on Kubernetes
- Strong understanding on LLM inference features, including structured output, KV-cache, and LoRa adapter
- Hands-on experience building and running GPU workloads in k8s, including NVIDIA device plugin, MIG, CUDA drivers/runtime, and resource isolation
Responsibilities
- 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
Other
- A degree in Computer Science, Computer Engineering, or a related field (BS or MS) or equivalent experience
- Excellent collaboration and communication skills; ability to influence cross-functional design
- Ability to work with diverse teams
- Commitment to fostering a diverse work environment
- Adherence to NVIDIA's equal opportunity employment practices
