Logic Analyzers Data Jobs

1 job found

2d ago

Applied AI Engineer

NVIDIA San Francisco, CA

San Francisco, CA

2d ago

$152k - $288k/yr Full time Electrical Engineering Agentic Ai AI

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Job Description

The Applied AI Engineer role within NVIDIA's Silicon Co-Design Group focuses on architecting, developing, and deploying AI-powered solutions to enhance the silicon design and automation toolchain.

Responsibilities

LLM powered validation pipelines: design and deploy AI systems that accelerate post-silicon validation across semiconductor environments, prioritizing the creation of next-generation capabilities over maintaining existing ones.
Cross-team AI integration: collaborate with multi-functional engineering teams to identify friction points where AI can add value, then build scalable solutions with broad impact across products and silicon generations.
Technology scouting and evaluation: assess emerging AI frameworks and architectures, making a compelling case for those worth adopting ahead of industry peers.
Impact measurement and continuous improvement: develop data systems to quantify AI impact, establish clear performance indicators, close gaps, and drive iterative improvements across the organization.

Requirements

PhD in CS, Electrical Engineering, Computer Engineering, or a related field, or equivalent experience, with 5+ years of hands-on ML/AI system development 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 to production deployment.
Strong Python skills and proficiency in at least one statically typed language such as C, C++, C#, Java, or Scala.
Experience in a silicon development environment with exposure to chip and system characterization methodologies, process variation, statistical error rates, or advanced timing and power analysis.
Hands-on silicon bring-up, characterization, or lab debugging using standard tools (e.g., oscilloscopes, multimeters, logic analyzers).
Solid EE fundamentals including computer architecture, high-speed interfaces, timing, power basics, and understanding of firmware/driver structures and hardware interaction.
Proven ability to balance multiple concurrent projects with strong problem-solving, communication, and teamwork skills.

Technologies

Python, C, C++, C#, Java, Scala
PyTorch, TensorFlow
NeMo Agent Toolkit, LangChain, Semantic Kernel, AutoGen, CrewAI, n8n
Oscilloscopes, Multimeters, Logic Analyzers

Compensation & Location

Location: California, hybrid
Salary: USD 152,000 - 287,500 per year
Minimum experience: 5 years
Education: PhD

Benefits

Equity
Benefits
Competitive salaries

Ways to Stand Out From the Crowd

Experience debugging complex system-level issues involving hardware and software interactions, with leadership or ownership in root-cause analysis of silicon or feature-level problems.
Ability to translate innovative AI research into practical, high-impact production tools.
Familiarity with modern AI technologies and methodologies for crafting and launching LLMs.
Experience building and deploying orchestration agents that manage hundreds to thousands of tools.
Hands-on experience with deep learning frameworks like PyTorch or TensorFlow, and practical use of agentic and orchestration tools including NeMo Agent Toolkit, LangChain, Semantic Kernel, AutoGen, CrewAI, or n8n.

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