Senior DFX Software Engineer - Machine Learning at NVIDIA

Department: Engineer, Sys SW

Compensation

$152,000 – $287,500/yr

Setup: On-site
Location: California
Type: Full-time
Level: senior
Posted: Aug 18, 2026

Description

NVIDIA is hiring a Senior DFX Software Engineer - Machine Learning to develop high-performance software for silicon device testing, silicon debug, and silicon failure analysis. The role focuses on test pattern generation, parallel graph traversal and analysis, and the application of large language models, RAG, graph-based machine learning, and reinforcement learning. Candidates need a BS in EE or CS or equivalent experience, at least five years of software development experience, strong Python or C++ skills, and expertise in DFT, simulations, failure analysis, and large-scale machine learning systems. The base salary range is 152,000 USD to 241,500 USD for Level 3 and 184,000 USD to 287,500 USD for Level 4, with equity and benefits; applications were accepted until August 22, 2026.

Required Skills

Python
C++
LLMs
RAG
Graph ML
Reinforcement learning
DFT
Failure analysis
PPO
SAC
Q-learning
Spark

Additional Information

Minimum Education: Bachelor of Science in Electrical Engineering or Computer Science, or equivalent experience
Required Previous Experiences: At least 5 years of software development experience
Experience using LLMs, GNNs, and reinforcement learning for efficient EDA solutions
Expertise in high-performance algorithms for DFT, simulations, and failure analysis
Hands-on experience with large-scale training and data processing using ZeRO and Spark
Preferred Qualifications: Master's degree or higher
Hands-on development in modern C++
Deployment of large-scale agentic applications with high concurrency and agility
Experience with software and hardware involving DFT, failure analysis, and CAD tools
Experience with agentic models, frameworks, observability, and evaluation tools
In-depth understanding of graph neural networks and reinforcement learning for logic design automation
Experience fine-tuning large language models, building multi-agent systems, RAG pipelines, and vector databases