Applied AI Engineer

Job Title

Applied AI Engineer

Role Summary

Join NVIDIA's Silicon Co-Design Group to design, implement, and integrate AI solutions into chip design and automation workflows. The role focuses on building LLM-powered validation, automation, and data systems that accelerate silicon development and post-silicon validation.

Experience Level

Mid-level (Level 3/Level 4). The role expects 5+ years of experience building and deploying ML/AI systems or data-intensive backend services, including at least 2 years owning applied AI/LLM workflows end-to-end.

Responsibilities

Key responsibilities include designing and delivering AI systems for semiconductor workflows and collaborating across engineering teams to deploy production-grade AI solutions.

• Architect and deploy LLM-powered validation pipelines to speed post-silicon validation and make workflows more scalable and robust.
• Integrate AI solutions across multi-functional teams to remove friction and automate engineering workflows.
• Scout and evaluate emerging AI frameworks and architectures; recommend and prototype promising technologies.
• Build data and measurement systems to quantify AI impact and drive continuous improvement.
• Ship prototypes through production deployment, including monitoring, debugging, and iteration in production environments.

Requirements

Must-have technical skills and experience for immediate contribution.

• 5+ years of hands-on experience building and deploying ML/AI systems or data-intensive backend services.
• 2+ years owning an applied AI agent, LLM-powered workflow, or intelligent automation system from prototype to production.
• Strong Python skills and proficiency in at least one statically typed language (C, C++, C#, Java, or Scala).
• Experience deploying, monitoring, and debugging scalable AI/ML models in production.
• Solid electrical engineering fundamentals: computer architecture, high-speed interfaces, timing, and power basics; familiarity with firmware/driver structures and hardware interaction.
• Experience in a silicon development environment, including chip and system characterization methodologies.
• Hands-on lab debug and bring-up experience with tools such as oscilloscopes, multimeters, and logic analyzers.
• Proven ability to manage multiple projects, solve complex problems, and communicate effectively across teams.

Education Requirements

BS, MS, or PhD in Computer Science, Electrical Engineering, Computer Engineering, or a related technical field — or equivalent practical experience.

Nice-to-have

Additional skills that strengthen a candidate's profile.

• Experience translating AI research into production tools and launching LLMs.
• Familiarity with deep learning frameworks such as PyTorch or TensorFlow.
• Hands-on experience with agentic and orchestration tools (NeMo Agent Toolkit, LangChain, Semantic Kernel, AutoGen, CrewAI, n8n).
• Track record debugging complex system-level HW/SW interactions and driving root-cause analysis for silicon or feature issues.

About the Company

Company: NVIDIA

Headquarters: Santa Clara, California, USA

NVIDIA is a global leader in accelerated computing, renowned for its innovative solutions in AI and digital twins that transform diverse industries. The company specializes in networking technologies, providing end-to-end InfiniBand and Ethernet solutions for servers and storage that optimize performance and scalability. NVIDIA serves sectors such as high-performance computing, enterprise data centers, and cloud computing, constantly reinventing its products and services to stay ahead in the market.