Senior Applied Machine Learning Engineer - Vlsi Design

NVIDIA NVIDIA · Semiconductors · Santa Clara, CA

NVIDIA is seeking a Senior Applied Machine Learning Engineer to build AI-driven software systems for circuit design, combining automation algorithms, DL models, and agentic workflows. The role involves working on pre-silicon and post-silicon hardware design data, circuit optimization, and AI systems for EDA/design automation, translating requirements into AI/ML and agentic system problems, and testing/releasing models and AI systems.

What you'd actually do

  1. Work 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/design automation.
  2. Work on applications ranging from silicon data analysis, manufacturing process variation analysis, VLSI circuit design, timing, and agent-driven design exploration and agent flow optimization.
  3. Translate requirements into data science, AI/ML, and agentic system problems; architect and build solutions.
  4. Test and release models and AI systems that integrate with existing machine learning, design automation, and visualization tools within the organization.
  5. Analyze datasets, raise and validate hypotheses, extract relevant features, and build models and self-improving workflows on top of them.

Skills

Required

  • MS/PhD in Electrical/Computer Engineering, Computer Science, Applied Mathematics, or equivalent experience
  • 4+ years experience in circuit design, VLSI, ASIC, EDA, silicon analysis, or custom circuit design
  • Applied Math/ML/Software programming
  • Python
  • C++

Nice to have

  • deep learning algorithms
  • AI agent frameworks
  • PyTorch
  • LangChain
  • LangGraph
  • AI systems for EDA
  • design automation
  • circuit design workflows
  • AI-driven EDA
  • circuit optimization
  • design-space exploration
  • autonomous design systems
  • agentic systems
  • autonomous optimization loops
  • self-improving AI systems
  • production-scale AI/ML platforms

What the JD emphasized

  • 4+ years experience in circuit design, VLSI, ASIC, EDA, silicon analysis, or custom circuit design is required
  • 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

Other signals

  • AI-driven software systems for circuit design
  • agentic workflows to accelerate end-to-end design automation
  • AI systems for EDA/design automation
  • agent-driven design exploration and agent flow optimization
  • build models and self-improving workflows