Senior AI Systems Engineer, Chip Design

NVIDIA•Austin, TX

1d•$184,000 - $356,500

About The Position

NVIDIA is seeking a Senior AI Systems Engineer to develop and deploy AI agents that use machine learning models to solve complex problems in VLSI design. The engineer will work with experts in VLSI design, machine learning, and software engineering to create and integrate machine-learning-based solutions that improve the efficiency, productivity, and quality of VLSI design flows. The position involves applying AI agents and learning-based methods to complex engineering workflows, developing production-quality software, and helping advance AI-driven design methodologies. The role requires collaboration and the ability to turn complex design challenges into agent-driven solutions. The stated base salary ranges are $184,000–$287,500 for Level 4 and $224,000–$356,500 for Level 5. The employee is also eligible for equity and benefits.

Requirements

BS, MS, PhD, or equivalent experience in Computer Science, Electrical or Computer Engineering, or a related field.
At least 6 years of experience building AI-driven software systems, ideally applied to complex engineering workflows.
Strong Python programming skills and experience developing production-quality systems.
Demonstrated experience designing and applying AI agents or learning-based decision systems, such as reinforcement learning, planning, or LLM-based agents, to optimize processes.
Proficiency with modern machine-learning frameworks such as PyTorch or TensorFlow and data-driven model development.
Strong problem-solving and collaboration skills, including the ability to translate complex design challenges into agent-driven solutions.

Nice To Haves

Experience with Large Language Models (LLMs) and their applications in software and AI development.
Proficiency in software development methodologies, including version control, testing, and CI/CD.
Strong interest in learning disparate concepts and combining them in innovative ways.

Responsibilities

Create and integrate AI agents to improve the efficiency, productivity, and quality of VLSI design flows.
Collaborate on the design and implementation of algorithms and models to optimize VLSI design processes.
Contribute to software tools and frameworks that support integrating AI into VLSI design.
Analyze and interpret data to identify patterns and insights that inform AI-driven design methodologies.
Keep up with advances in machine learning, deep learning, and VLSI build to continuously improve solutions.