NVIDIA
From NVIDIA's careers page
Status: listed on the employer's own careers page when we last checked (daily). Confirm on their site before applying.
You will also be eligible for equity and benefits.
We are now looking for a Senior DFX Software Engineer - Machine Learning. Do you like to think creatively and enjoy solving challenges that require innovation? If so, we may have an opportunity for you. On our team we define and build methodologies, software, and flows tailored to the field of silicon device testing, silicon debug, and silicon failure analysis. We owe our success to our people, some of the brightest in the world, and a company culture that fosters and encourages innovation, and fuels our creativity!
Our team contributes to the advancement of all the fields in which NVIDIA participates, from gaming to building groundbreaking state-of-the-art compute platforms and Artificial Intelligence, by enabling high quality Silicon defect screening to sustain all these fields. This often requires new ways of thinking in order to meet new challenges, and we pride ourselves in our ability to tackle these challenges in ways that enable our success. If you are a like-minded person who enjoys innovation and likes to solve technical challenges then we would love to hear from you!
Develop high performance software to enable design and development of efficient test pattern generation, application of these patterns on Silicon, failure analysis, and yield learning
Create efficient parallel graph traversal and graph analysis techniques
Work with multi-functional teams to assess and tackle problems that involve multiple areas of expertise through the company
Apply LLMs, RAGs, graph-based ML approaches, and reinforcement learning to define innovative solutions
BS in EE or CS (or equivalent experience); MS or higher degree preferred
5+ years of experience in Software development
Strong programming experience in Python or C++. Hands on development in modern C++ is a huge plus.
Experience use of LLMs (Large Language Models), GNNs (Graph Neural Networks), and Reinforcement Learning for efficient EDA solution.
Expertise in high performance algorithms for DFT, simulations, and failure analysis.
Understanding of different agent architectures, RAG systems, and communication protocols
Deep familiarity with reinforcement learning algorithms like PPO, SAC, or Q-learning, including experience tuning hyper-parameters and reward functions
Hands on experience with large scale training (e.g., ZeRO) and data processing (e.g. Spark)
Excellent communication skills
Proven deployment of large-scale agentic application with high concurrency and agility
Experience with software and hardware especially involving DFT, failure analysis, and CAD tools
Working experience of agentic models / frameworks, observability and evaluation tools
In-depth understanding of the graph neural networks, and reinforcement learning for logic design automation
Experience with fine-tuning large language models, building advanced multi-agent systems, RAG pipelines and vector databases
NVIDIA offers highly competitive salaries and a comprehensive benefits package. We have some of the most brilliant and talented people in the world working for us and, due to unprecedented growth, our world-class engineering teams are growing fast. If you're a creative and autonomous engineer with real passion for technology, we want to hear from you.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until November 3, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
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