Hardware - Physical Engineering (PI/PD) Engineer

Job Title

Hardware - Physical Engineering (PI/PD) Engineer

Role Summary

Join the hardware team to support physical implementation and performance, power, area (PPA) planning for FuriosaAI's inference-focused ASICs. The role focuses on PI/PD tasks across synthesis, timing closure, and implementation verification.

Work closely with internal architecture, RTL teams and external design houses to validate design trade-offs and deliver manufacturable tapeouts.

Experience Level

Mid-level — typically 2+ years industry experience (see requirements for specifics).

Responsibilities

Core responsibilities include physical implementation verification, timing, and collaboration with design partners.

• Evaluate PPA (performance, power, area) as part of chip architecture and planning.
• Perform synthesis and logic equivalence checking (LEC).
• Develop SDC and UPF constraints and run static timing analysis (STA).
• Support signoff flows and work with EDA tools for implementation verification.
• Collaborate with external design houses and cross-functional teams to resolve implementation issues.

Requirements

Must-have technical skills and relevant industry experience; preferred items listed separately.

• Proficient in Verilog HDL for digital logic design.
• 2+ years industry experience with logic synthesis, LEC, STA, and producing SDC & UPF.
• Experience with EDA toolchains (Synopsys tools such as DC, Formal/MCDC flows, PrimeTime) and scripting (TCL, shell).
• Ability to work effectively with external design houses and cross-functional teams.
• Nice-to-have: DFT, place-and-route experience; experience with high-speed connectivity IPs (PCIe, Ethernet, HBM); 5+ years ASIC design experience.

Education Requirements

Bachelor's degree in Electronic Engineering or another technically related field.

About the Company

Company: FuriosaAI

Headquarters: Seoul, South Korea

FuriosaAI develops high-performance, energy-efficient AI inference hardware and software. Founded in 2017 by semiconductor and AI engineers, the company builds AI-native compute platforms to reduce AI energy and operational costs and operates globally with offices in Korea, Silicon Valley, and an R&D lab in Lisbon.