Applied AI Engineer

Overview In this role, you architect and ship AI-enabled workflows that accelerate post-silicon validation and optimize chip design tooling. You collaborate with cross-functional teams to deploy scalable AI solutions that impact multiple silicon generations. You evaluate new AI frameworks and drive measurable improvements with data-driven insights. This position offers the opportunity to shape NVIDIA’s AI-driven design tooling and contribute to high-impact production-scale systems. Compensation / Benefitsequitybenefitsopportunities for career growthremote/flexible work options (location-based)health and retirement benefitscareer development programs ResponsibilitiesDesign and deploy LLM-powered validation pipelines to speed and scale post-silicon validationIntegrate AI across multi-functional teams to remove friction and deliver wide impactEvaluate emerging AI frameworks and architectures and advocate for adoptionBuild data systems to measure AI impact, close performance gaps, and drive continuous improvement Key requirementsBS, MS, or PhD in CS, EE, CE, or related field with 5+ years in ML/AI or data-intensive backend services2+ years of direct Applied AI experience owning an AI agent, LLM-powered workflow, or intelligent automation end-to-endStrong Python skills and proficiency in at least one static language (C, C++, C#, Java, or Scala)Proven track record deploying, monitoring, and debugging scalable AI/ML modelsStrong EE fundamentals including computer architecture, high-speed interfaces, timing, power, and firmware/driver understandingExperience in a silicon development environment with chip/system characterization and lab debug toolsproblem-solvingclear communicationcollaborationPythonC/C++/Java/Scala (static language)ML deployment and monitoring