Applied AI Engineer

🔥 1 hour ago

🌵 Arizona, California, +1 more states – Remote

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

💵 $152k - $241.5k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 AI Engineer

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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

• 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

• 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

• Equity • Benefits