Ai/ml Physical Design Flow Engineer

Tenstorrent · Semiconductors · Austin, Fort Collins +1 · Advanced Physical Design

The role involves architecting, integrating, and deploying AI/ML-driven solutions into production physical design flows for advanced semiconductor nodes. This includes creating custom CAD tools and optimizing EDA tools using data-driven and ML-based techniques to improve PPA and runtime. The engineer will also develop and enhance RTL-to-GDS methodologies.

What you'd actually do

  1. Lead and contribute to cross-functional efforts solving complex physical design challenges across IPs, projects, and advanced technology nodes.
  2. Develop and enhance RTL-to-GDS methodologies, including floorplanning, synthesis, P&R, STA, signoff, and assembly.
  3. Architect and deploy AI/ML-driven solutions in production flows to improve engineering efficiency, turnaround time, and QoR.
  4. Optimize EDA tools and custom CAD flows using data-driven and ML-based techniques, in close collaboration with verification, extraction, timing, DFT, and EDA vendors.

Skills

Required

  • Physical Design CAD methodology at advanced nodes
  • PPA and/or runtime improvements on high-performance, low-power taped-out designs
  • industry-standard EDA tools (e.g., Fusion Compiler) across synthesis, P&R, STA, signoff, and hierarchical flows
  • Python/Tcl and data skills
  • ML frameworks (PyTorch, TensorFlow)

Nice to have

  • experience in ML frameworks (PyTorch, TensorFlow)

What the JD emphasized

  • advanced nodes
  • AI/ML-driven solutions
  • production flows
  • ML-based techniques

Other signals

  • AI/ML-driven solutions into production physical design flows
  • custom CAD tools
  • ML-enabled capabilities
  • AI/ML-driven solutions in production flows
  • ML-based techniques