Senior DFX Software Engineer - Machine Learning

at Nvidia

USD 152,000-287,500 per year

SENIOR

✅ On-site

Tech Stack
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

AI Algorithms @ 3 Communication @ 4 LLM Machine Learning Observability @ 4 Python @ 1 RAG @ 4 Reinforcement Learning @ 4 Software Development @ 6 Spark @ 4 Vector Databases @ 4

Details

The team defines and builds methodologies, software, and flows for silicon device testing, silicon debug, and silicon failure analysis. The work supports high-quality silicon defect screening across NVIDIA's gaming, compute, and artificial intelligence platforms.

Responsibilities

Develop high-performance software for efficient test pattern generation, silicon pattern application, failure analysis, and yield learning.
Create efficient parallel graph traversal and graph analysis techniques.
Collaborate with multifunctional teams to solve problems involving multiple areas of expertise.
Apply large language models (LLMs), retrieval-augmented generation (RAG), graph-based machine learning, and reinforcement learning to develop innovative solutions.

Requirements

Bachelor's degree in electrical engineering, computer science, or equivalent experience; a master's degree or higher is preferred.
At least 5 years of software development experience.
Strong programming experience in Python or C++; hands-on development in modern C++ is a significant advantage.
Experience using LLMs, graph neural networks (GNNs), and reinforcement learning for efficient electronic design automation (EDA) solutions.
Expertise in high-performance algorithms for design-for-test (DFT), simulations, and failure analysis.
Understanding of agent architectures, RAG systems, and communication protocols.
Deep familiarity with reinforcement learning algorithms such as PPO, SAC, and Q-learning, including tuning hyperparameters and reward functions.
Hands-on experience with large-scale training, such as ZeRO, and data processing, such as Spark.
Excellent communication skills.

Preferred Qualifications

Proven 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 and frameworks, observability tools, and evaluation tools.
In-depth understanding of graph neural networks and reinforcement learning for logic design automation.
Experience fine-tuning large language models and building advanced multi-agent systems, RAG pipelines, and vector databases.

Compensation and Benefits

Base salary range of $152,000–$241,500 for Level 3.
Base salary range of $184,000–$287,500 for Level 4.
Eligibility for equity and benefits.
Applications will be accepted at least until August 22, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is an equal opportunity employer committed to an inclusive work environment.