Senior Applied Machine Learning Engineer - VLSI Design

Senior Applied Machine Learning Engineer specializing in VLSI design automation at NVIDIA. The role focuses on building data science and AI driven systems to accelerate pre-silicon and post-silicon hardware design and circuit optimization, with integration into existing EDA tools and workflows.

Responsibilities

• Collaborate within a multi-functional team on projects involving pre-silicon and post-silicon hardware design data, circuit optimization, SPICE correlation, and AI systems for EDA and design automation.
• Develop applications spanning silicon data analysis, manufacturing process variation analysis, VLSI circuit design, timing, and agent-driven design exploration and flow optimization.
• Translate requirements into data science, AI/ML, and agentic system problems; architect and implement robust solutions.
• Test and deploy models and AI systems that integrate with existing machine learning, design automation, and visualization tools across the organization.
• Analyze datasets, formulate and validate hypotheses, extract relevant features, and construct models and self-improving workflows on top of them.
• Refine models, algorithms, and autonomous optimization systems to achieve the desired QOR.

Requirements

• MS or PhD in Electrical/Computer Engineering, Computer Science, Applied Mathematics, or equivalent experience.
• 4+ years of experience in circuit design, VLSI, ASIC, EDA, silicon analysis, or custom circuit design.
• Experience in Applied Math, ML, or software programming with proven ability in Python and C++.
• Experience with deep learning algorithms, AI agent frameworks, and tools such as PyTorch, LangChain, or LangGraph is a definite plus.

Technologies

• Python
• C++
• PyTorch
• LangChain
• LangGraph

Benefits

• Equity
• Benefits

Ways to Stand Out From the Crowd

• Experience building AI systems for EDA, design automation, or circuit design workflows.
• Research or project experience in AI-driven EDA, circuit optimization, design-space exploration, or autonomous design systems.
• Experience building agentic systems, autonomous optimization loops, self-improving AI systems, or production-scale AI/ML platforms.
• Effective verbal and written communication and technical presentation skills.
• Self-starter with a passion for growth, continuous learning, and sharing findings across the team.