AI/ML Physical Design Engineer — PPA & RTL-to-GDS

Tenstorrent University Jobs; Santa Clara (CA); Híbrido; USD 100.000 - 500.000; Jornada completa

Descripción de la vacante

Tenstorrent is seeking a Physical Design Engineer to lead cross-functional efforts solving complex physical design challenges and to develop RTL-to-GDS methodologies across advanced nodes, with a strong focus on PPA and runtime improvements.

The engineer will architect and deploy AI/ML-driven solutions in production CAD flows, create custom tools, and collaborate with internal teams and EDA vendors to drive next‑generation capabilities.

Formación

• BS in Electrical or Computer Engineering (or equivalent experience) with 5+ years in Physical Design CAD methodology.
• Proven track record improving PPA and/or runtime on high-performance, low-power taped-out designs.
• Hands-on with industry-standard EDA tools (Fusion Compiler) across synthesis, P&R, STA, signoff, and hierarchical flows.
• Strong Python/Tcl and data skills, with interest or experience in ML frameworks (PyTorch, TensorFlow).

Responsabilidades

• Lead and contribute to cross-functional efforts solving complex physical design challenges across IPs, projects, and advanced technology nodes.
• Develop and enhance RTL-to-GDS methodologies, including floorplanning, synthesis, P&R, STA, signoff, and assembly.
• Architect and deploy AI/ML-driven solutions in production flows to improve engineering efficiency, turnaround time, and QoR.
• 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.

Conocimientos

Python

Tcl

Data skills

ML frameworks

Educación

BS in Electrical or Computer Engineering

Herramientas

Fusion Compiler

Descripción del empleo

Tenstorrent is seeking a Physical Design Engineer to lead cross-functional efforts solving complex physical design challenges and to develop RTL-to-GDS methodologies across advanced nodes, with a strong focus on PPA and runtime improvements.

The engineer will architect and deploy AI/ML-driven solutions in production CAD flows, create custom tools, and collaborate with internal teams and EDA vendors to drive next‑generation capabilities.