Senior DFX Software Engineer - Machine Learning

Job Title

Senior DFX Software Engineer - Machine Learning

Role Summary

The role develops software and methodologies for silicon device testing, silicon debug, failure analysis, and yield learning. The team builds tools and flows to enable defect screening and to support design verification and failure root-cause analysis across NVIDIA platforms.

Experience Level

Senior — typically 5+ years of software development experience.

Responsibilities

Primary responsibilities include:

• Design and implement high-performance software for test pattern generation, pattern application on silicon, and failure analysis workflows.
• Create efficient parallel graph traversal and graph analysis techniques for EDA and failure-debug tasks.
• Apply LLMs, retrieval-augmented generation (RAG), graph-based ML, and reinforcement learning to propose and implement solutions.
• Collaborate with cross-functional teams to define requirements and integrate multi-domain solutions.
• Scale training and data pipelines and optimize performance for large datasets and models.

Requirements

Core qualifications and skills required:

• 5+ years of professional software development experience.
• Strong programming skills in Python or C++; hands-on modern C++ development is a plus.
• Experience using LLMs, graph neural networks (GNNs), and reinforcement learning in EDA or related applications.
• Expertise with high-performance algorithms relevant to DFT, simulations, and failure analysis.
• Understanding of agent architectures, RAG systems, and inter-component communication protocols.
• Familiarity with reinforcement learning algorithms (PPO, SAC, Q-learning) and experience tuning hyperparameters and reward functions.
• Hands-on experience with large-scale model training techniques (e.g., ZeRO) and large-scale data processing frameworks (e.g., Spark).
• Excellent written and verbal communication skills.

Nice-to-have:

• Proven deployment of large-scale, agentic applications with high concurrency.
• Experience with software/hardware integration for DFT, failure analysis, and CAD tools.
• Working experience with multi-agent frameworks, observability, and evaluation tooling.
• Experience fine-tuning large language models, building RAG pipelines, or using vector databases.

Education Requirements

BS in Electrical Engineering or Computer Science (or equivalent practical experience) is expected; MS or higher degree preferred. Equivalent industry experience is acceptable where stated.

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.