Applied AI Engineer

🕒 August 11

🌵 Arizona, California, +2 more states – Remote

🌵 Arizona – Remote 🏄 California – Remote 🐊 Florida – Remote 🤠 Texas – Remote

💵 $152k - $287.5k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 AI Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 11%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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NVIDIA

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1993

🏥 Healthcare

🏭 Manufacturing

🤖 Artificial Intelligence

Healthcare • Manufacturing • Artificial Intelligence

NVIDIA is a leading technology company specializing in accelerated computing and artificial intelligence. NVIDIA pioneers advancements in graphical processing units (GPUs), cloud computing, data centers, and virtual reality, with a focus on gaming, automotive, healthcare, and robotics industries. The company's innovations, such as NVIDIA Omniverse, transform traditional digital processes by enabling high-fidelity simulations and rendering tasks. Their applications span various industries, from autonomous vehicles using NVIDIA DRIVE to healthcare solutions with NVIDIA Clara, and AI-driven analytics and workflows.

📋 Description

• Architect and implement AI solutions for NVIDIA’s chip design and automation infrastructure • Design and deploy LLM-powered validation pipelines to make post-silicon validation faster, smarter, and more scalable • Work directly with multifunctional engineering teams to identify AI opportunities and build solutions • Evaluate emerging AI frameworks and architectures and make adoption recommendations • Build data systems to measure AI impact quantitatively • Establish performance indicators, close performance gaps, and drive continuous improvement • Drive initiatives from concept through production deployment

🎯 Requirements

• BS, MS, or PhD or equivalent experience in CS, EE, CE, or a related field • 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 • Strong Python skills • Proficiency in at least one static language such as C, C++, C#, Java, or Scala • Strong EE fundamentals, including computer architecture, high-speed interfaces, timing, power basics, and firmware/driver structures and hardware interaction • Hands-on experience in production test, system validation, post-silicon bring-up, reliability, silicon debug, or silicon productization areas such as ATE, SLT, board-level test, validation, or yield analysis • Experience working within a silicon development environment, with exposure to chip and system characterization methodologies • Familiarity with manufacturing and quality metrics such as yield, FPY, DPPM, RAS, TTR, and escape rate • Proven track record in balancing multiple concurrent projects • Exposure to GPU, CPU, AI accelerator, networking, automotive, or other large-scale SoC programs • Familiarity with modern AI technologies and methodologies for crafting and launching LLMs • Experience building and deploying orchestration agents managing hundreds to thousands of tools • Ability to translate innovative AI research into practical, high-impact production tools • Demonstrated experience with deep learning frameworks like PyTorch or TensorFlow • Hands-on experience with agentic and orchestration tools, including NeMo Agent Toolkit, LangChain, Semantic Kernel, AutoGen, CrewAI, or n8n

🏖️ Benefits

• Equity • Benefits package