AI Platform Engineer

NVIDIA•Us, CA

About The Position

NVIDIA is looking to hire a deeply technical, creative, and AI Platform Engineer to build, support, and maintain the next generation of AI-powered enterprise products that improve engineering efficiency, data security, and power our product development. This role will give you the opportunity to collaborate with Cloud and AI/ML teams in a multifaceted and agile environment. You will be pivotal in shaping the technological future of our organization, ensuring our systems are scalable, reliable, and ready for the AI era. What you will be doing: 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.

Requirements

10+ years of experience in cloud, platform, or SRE roles.
Bachelors 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.
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.

Nice To Haves

Deep experience with AI/ML platforms (e.g., Hugging Face, Weights & Biases, NVIDIA NIM).
Proven use of AI agents and LLM tooling to enhance observability, incident response, or developer productivity.
Experience with artifact management, AI supply chain security, or trusted model distribution systems.
Strong ownership demeanor with a structured, automation-first approach.
Demonstrated impact driving AI-first engineering practices across teams.

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.