2 days ago
Santa Clara, CA, USASenior / Staff+
H1B sponsor
Base Salary
$152k - $288k/yr
Responsibilities
- Design and deploy LLM-powered AI systems that improve post-silicon validation across semiconductor environments.
- Partner with multifunctional engineering teams to identify opportunities for AI-driven automation and build production solutions.
- Evaluate emerging AI frameworks and architectures and recommend technologies for adoption.
- Build data systems, quantitative impact indicators, and continuous-improvement processes for AI initiatives.
- Own applied AI agents, LLM-powered workflows, or intelligent automation systems from prototype through production deployment.
Requirements
- BS, MS, PhD, or equivalent experience in computer science, electrical engineering, computer engineering, 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 and proficiency in at least one of C, C++, C#, Java, or Scala.
- Strong electrical engineering fundamentals covering computer architecture, high-speed interfaces, timing, power basics, firmware/driver structures, and hardware interaction.
- Hands-on experience in production test, system validation, post-silicon bring-up, reliability, silicon debug, silicon productization, ATE, SLT, board-level test, or yield analysis.
- Experience in a silicon development environment and familiarity with chip/system characterization and manufacturing or quality metrics.
- Preferred experience with GPU, CPU, AI accelerator, networking, automotive, or large-scale SoC programs.
- Preferred familiarity with LLM development, orchestration agents, deep learning frameworks, and agentic orchestration tools.
- Preferred experience translating AI research into practical production tools.
Benefits
- Competitive base salary and equity eligibility.
- Generous benefits package.
- Hybrid work arrangement, as indicated by the #LI-Hybrid designation.
Categories
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.