Senior Staff AI Platform Engineer

at Nvidia

USD 168,000-322,000 per year

SENIOR

✅ On-site

Tech Stack
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

AI @ 7 Agile Algorithms @ 6 Communication @ 6 Data Structures @ 6 Debugging @ 7 Distributed Systems @ 7 GPU @ 4 Go @ 7 Kubernetes @ 7 LLM MLOps @ 4 Machine Learning Observability @ 7 Python @ 7 Rust @ 7 SRE @ 8 Security @ 4

Details

NVIDIA is looking to hire a deeply technical, creative, and Senior AI Platform Engineer to build, support, and maintain the next generation of AI-powered enterprise products that improve engineering efficiency, data security, and power product development. This role collaborates with Cloud and AI/ML teams in a multifaceted and agile environment. You will shape the technological future of the organization by ensuring systems are scalable, reliable, and ready for the AI era.

Responsibilities

Define and lead AI-native infrastructure roadmaps and cross-organizational initiatives.
Architect and scale LLM/ML infrastructure across cloud-native clusters and on-premises hardware.
Design and implement observability for infrastructure health and AI model performance.
Build LLM-aware monitoring and leverage AI to improve incident response and reduce toil.
Develop automation and tooling to ensure reliability, scalability, and developer self-services.
Troubleshoot complex distributed systems, including deep Kubernetes and AI/ML scaling challenges.
Drive AI-assisted engineering practices and mentor engineers to foster an AI-first culture.
Partner with product engineering and internal business units to translate AI platform capabilities into reliable, scalable solutions that accelerate product development.

Requirements

10+ years in cloud, platform, or SRE roles with relevant education or equivalent experience.
Bachelor’s degree or equivalent experience.
Strong Python and at least one systems language (C++, Go, or Rust), with proven distributed systems debugging expertise.
Deep experience building and scaling distributed systems, including Kubernetes and bare-metal infrastructure.
Strong observability design across infrastructure and AI workloads (metrics, logging, tracing, AI quality signals).
Hands-on experience operating AI/ML platforms, including MLOps, model serving, and GPU-accelerated environments.
Experience with infrastructure and application security practices, such as identity/auth, network segmentation, supply chain security, and vulnerability management in cloud-native environments.
Practical use of AI-assisted development tools and coding agents in daily workflows.
Solid foundation in data structures, algorithms, and complexity analysis.
Excellent problem-solving, communication, and collaboration across multiple functions.