Applied AI Engineer

NVIDIA

Applied AI Engineer developing AI solutions integrated into NVIDIA's chip design and automation infrastructure. Leading initiatives from concept to deployment in a dynamic work environment.

Posted 7/28/2026full-timeRemote • Arizona, California, Florida, Texas • 🇺🇸 United StatesMid-LevelSenior💰 $152,000 - $287,500 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and deploying AI systems within semiconductor environments, with a strong foundation in machine learning and data-intensive backend services. Proficient in Python and at least one static programming language, with hands-on experience in silicon development and characterization methodologies.

Highest-signal resume keywords

AI System Design and DeploymentMachine Learning/AI ExperiencePython ProgrammingSilicon Development EnvironmentData-Intensive Backend Services

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningArtificial IntelligencePythonCC++C#JavaScalaSilicon CharacterizationAI Model Deployment

Soft Skills

Problem-SolvingCommunicationCollaboration

Tools & Technologies

OscilloscopesMultimetersLogic Analyzers

Industry Keywords

Post-Silicon ValidationChip CharacterizationFirmwareDriver StructuresHigh-Speed Interfaces

Tech Stack

Tools & technologies

JavaPythonScala

About the role

Key responsibilities & impact

Design and deploy AI systems that make post-silicon validation faster, smarter, and more scalable across semiconductor environments.
Work directly with multi-functional engineering teams across the organization to identify where AI can eliminate friction, and then build the solution.
Evaluate emerging AI frameworks and architectures before the rest of the industry catches on.
Build the data systems that prove what's working and establish clear, quantitative indicators of AI impact, close performance gaps, and drive iteration across the org to turn insight into lasting improvement!

Requirements

What you’ll need

BS, MS, or PhD or equivalent experience in CS, EE, CE, or a related field, with 5+ years of hands-on experience building and deploying ML/AI systems or data-intensive backend services.
2+ years of direct Applied AI experience independently owning an AI agent, LLM-powered workflow, or intelligent automation system end-to-end — from prototype through production deployment.
Strong Python skills and proficiency in at least one static language such as C, C++, C#, Java, or Scala.
Proven track record with deploying, monitoring, and debugging scalable AI/ML models.
Strong EE fundamentals, including computer architecture, high-speed interfaces, timing, power basics, and a solid understanding of firmware/driver structures and hardware interaction.
Experience working within a silicon development environment, with exposure to chip and system characterization methodologies.
Hands-on experience with silicon bring-up, characterization, or lab debug using standard tools (e.g., oscilloscopes, multimeters, logic analyzers).
Proven ability to balance multiple simultaneous projects with excellent problem-solving, communication, and collaboration skills.

Benefits

Comp & perks

Equity
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