Job Description

Overview

Senior Software Engineer - NIM Factory Container and Cloud Infrastructure at NVIDIA. We are seeking a Senior Software Engineer focused on container and cloud infrastructure to design and implement our core container strategy for NVIDIA Inference Microservices (NIMs) and hosted services. Build enterprise-grade software and tooling for container build, packaging, and deployment, and help improve reliability, performance, and scale across thousands of GPUs. This role includes work on disaggregated LLM inference and other deployment patterns.

What You'll Be Doing

• 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.

What We Need To See

• 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 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.
• 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 From The Crowd

• Expertise with Helm chart design systems, Operators, and platform APIs serving many teams.
• Experience with OpenAI API, Hugging Face API, and 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.

Compensation and Benefits

Your base salary will be determined based on location, experience, and market pay for similar roles. 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.

NVIDIA is committed to fostering a diverse work environment and is an equal opportunity employer. We value diversity and do not discriminate in hiring or promotion 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.

Applications for this job will be accepted at least until September 21, 2025.

Job Tags

Similar Jobs