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: 23 hours agoStatus: Live

Job Summary

Develop and integrate AI/ML solutions into NVIDIA’s chip design and automation toolchain, focusing on LLM-powered validation pipelines that make post-silicon validation faster, smarter, and more scalable. Partner with cross-functional engineering teams to identify where AI removes friction, scout and evaluate emerging AI frameworks, and build measurement systems to quantify impact and drive continuous improvement from prototype through production deployment.

Location: California, Arizona, Florida, Santa Clara

Workplace: Remote

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Design and deploy LLM-powered systems to accelerate post-silicon validation across semiconductor environments.
•Collaborate with cross-functional engineering teams to integrate AI where it removes friction across products and silicon generations.
•Evaluate emerging AI frameworks and architectures and drive decisions on what to adopt.
•Build data systems and quantitative indicators to measure AI impact, close performance gaps, and iterate across the organization.
•Continuously improve AI workflows from concept through deployment to enhance efficiency, scalability, and intelligence.

Pay and Benefits

Salary: USD 152,000 - 287,500 annually

Equity and Bonus:Equity

Key Requirements

•BS, MS, or PhD (or equivalent) in CS, EE, CE, or related field, with 5+ years building and deploying ML/AI systems or data-intensive backend services.
•2+ years of applied AI experience owning an AI agent, LLM-powered workflow, or intelligent automation system end-to-end from prototype through production.
•Strong Python skills and proficiency in at least one static language such as C, C++, C#, Java, or Scala.
•Proven track record deploying, monitoring, and debugging scalable AI/ML models.
•Strong EE fundamentals, including computer architecture, high-speed interfaces, timing/power basics, and understanding firmware/driver structures and hardware interaction.

Experience:5+ yearsMachine learningAISemiconductorLLMData-intensive backend services

Education:Bachelor's

Skills:Problem-solvingCommunicationCollaborationHands-on approach

Tech Stack:PythonCC++C#JavaScalaPyTorchTensorFlowNeMo Agent ToolkitLangChainSemantic KernelAutoGenCrewAIN8nLLMsOscilloscopesMultimetersLogic 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: 23 hours agoStatus: Live

Job Summary

Location: California, Arizona, Florida, Santa Clara

Workplace: Remote

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Design and deploy LLM-powered systems to accelerate post-silicon validation across semiconductor environments.
•Collaborate with cross-functional engineering teams to integrate AI where it removes friction across products and silicon generations.
•Evaluate emerging AI frameworks and architectures and drive decisions on what to adopt.
•Build data systems and quantitative indicators to measure AI impact, close performance gaps, and iterate across the organization.
•Continuously improve AI workflows from concept through deployment to enhance efficiency, scalability, and intelligence.

Pay and Benefits

Salary: USD 152,000 - 287,500 annually

Equity and Bonus:Equity

Key Requirements

•BS, MS, or PhD (or equivalent) in CS, EE, CE, or related field, with 5+ years building and deploying ML/AI systems or data-intensive backend services.
•2+ years of applied AI experience owning an AI agent, LLM-powered workflow, or intelligent automation system end-to-end from prototype through production.
•Strong Python skills and proficiency in at least one static language such as C, C++, C#, Java, or Scala.
•Proven track record deploying, monitoring, and debugging scalable AI/ML models.
•Strong EE fundamentals, including computer architecture, high-speed interfaces, timing/power basics, and understanding firmware/driver structures and hardware interaction.

Experience:5+ yearsMachine learningAISemiconductorLLMData-intensive backend services

Education:Bachelor's

Skills:Problem-solvingCommunicationCollaborationHands-on approach

Tech Stack:PythonCC++C#JavaScalaPyTorchTensorFlowNeMo Agent ToolkitLangChainSemantic KernelAutoGenCrewAIN8nLLMsOscilloscopesMultimetersLogic 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