NVIDIA

2 days ago

Applied AI Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 1 day agoStatus: Live

Job Summary

Build and deploy LLM-powered AI systems to accelerate post-silicon validation across NVIDIA’s semiconductor environments. Partner with multi-functional teams to integrate applied AI that removes friction in design and automation workflows, while scouting and evaluating emerging AI frameworks. Own the measurement and data systems that quantify AI impact and drive continuous improvement from prototype through production deployment.

Location: California, Georgia, Texas, Arizona, Florida, Santa Clara

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Design and deploy LLM-powered AI systems to make post-silicon validation faster, smarter, and more scalable.
•Collaborate with cross-functional engineering teams to identify where AI eliminates friction and build solutions end-to-end.
•Evaluate emerging AI frameworks and architectures and assess what to adopt.
•Build data systems and quantitative indicators to measure AI impact and drive iteration.
•Drive continuous improvement to turn insights into lasting workflow enhancements across products and silicon generations.

Pay and Benefits

Salary: USD 152,000 - 287,500 annually

Equity and Bonus:Equity

Perks:Equity

Key Requirements

•BS, MS, or PhD (or equivalent) in CS/EE/CE (or related), with 5+ years building and deploying ML/AI systems or data-intensive backend services.
•2+ years independently owning an Applied AI system (AI agent, LLM-powered workflow, or intelligent automation) end-to-end from prototype to production.
•Strong Python skills and proficiency in at least one static language such as C, C++, C#, Java, or Scala.
•Experience in a silicon development environment, including chip/system characterization, process variation, statistical error rates, or timing/power analysis.
•Hands-on silicon bring-up, characterization, or lab debugging using tools like oscilloscopes, multimeters, and logic analyzers.

Experience:5+ yearsMachine learningAISemiconductorsSilicon development

Education:Bachelor's

Skills:Problem-solvingCommunicationTeamworkContinuous improvementTechnology evaluation

Tech Stack:PythonCC++C#JavaScalaLLMPyTorchTensorFlowNeMo Agent ToolkitLangChainSemantic KernelAutoGenCrewAIN8nOscilloscopesMultimetersLogic analyzers

Company Brief

NVIDIA

Designs and manufactures GPUs, AI accelerators, and system-on-chip products for gaming, data centers, professional visualization, and automotive markets, enabling advanced graphics, AI, and high-performance computing solutions worldwide.

Industry: Electronics Manufacturing

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Santa Clara, United States

Founded: 1993

Glassdoor: 4.3

Website LinkedIn Glassdoor

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NVIDIA

2 days ago

Applied AI Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 1 day agoStatus: Live

Job Summary

Location: California, Georgia, Texas, Arizona, Florida, Santa Clara

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Design and deploy LLM-powered AI systems to make post-silicon validation faster, smarter, and more scalable.
•Collaborate with cross-functional engineering teams to identify where AI eliminates friction and build solutions end-to-end.
•Evaluate emerging AI frameworks and architectures and assess what to adopt.
•Build data systems and quantitative indicators to measure AI impact and drive iteration.
•Drive continuous improvement to turn insights into lasting workflow enhancements across products and silicon generations.

Pay and Benefits

Salary: USD 152,000 - 287,500 annually

Equity and Bonus:Equity

Perks:Equity

Key Requirements

•BS, MS, or PhD (or equivalent) in CS/EE/CE (or related), with 5+ years building and deploying ML/AI systems or data-intensive backend services.
•2+ years independently owning an Applied AI system (AI agent, LLM-powered workflow, or intelligent automation) end-to-end from prototype to production.
•Strong Python skills and proficiency in at least one static language such as C, C++, C#, Java, or Scala.
•Experience in a silicon development environment, including chip/system characterization, process variation, statistical error rates, or timing/power analysis.
•Hands-on silicon bring-up, characterization, or lab debugging using tools like oscilloscopes, multimeters, and logic analyzers.

Experience:5+ yearsMachine learningAISemiconductorsSilicon development

Education:Bachelor's

Skills:Problem-solvingCommunicationTeamworkContinuous improvementTechnology evaluation

Tech Stack:PythonCC++C#JavaScalaLLMPyTorchTensorFlowNeMo Agent ToolkitLangChainSemantic KernelAutoGenCrewAIN8nOscilloscopesMultimetersLogic analyzers

Company Brief

NVIDIA

Industry: Electronics Manufacturing

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Santa Clara, United States

Founded: 1993

Glassdoor: 4.3

Website LinkedIn Glassdoor