Physical Design Methodology Engineer, AI HW IP
Tenstorrent · Austin, Texas, United States; Belgrade, Serbia; Toronto, Ontario, Canada · Austin · Belgrade · Toronto
CHECKED 22H AGO
Infrastructureonsite$100k–$500k
At a glance
Highlights
- Own RTL-to-GDSII methodology powering AI IP physical design delivery.
- Build EDA automation for AI accelerators and high-performance CPUs.
- Influence EDA vendor roadmaps through direct technical partnership.
What they offer
- Highly competitive compensation package and benefits
Ideal candidate
Automation-minded physical design engineer who loves removing manual steps and building dependable flows. Collaborative partner who documents clearly and is curious about where AI genuinely improves methodology.
Requirements
- 5+ years developing and supporting physical design methodology or CAD flows in production use
- Expertise with FusionCompiler/ICC2, Innovus/Genus, PrimeTime, RedHawk and Tcl, Python, Perl scripting
- Deep understanding of advanced node methodology, low-power intent (UPF/CPF), CTS and signoff (EM/IR, DRC/LVS)
- Experience standing up flows for new nodes, PDKs, or foundry targets and qualifying new EDA releases
- remote policy
- hybrid
- hiring process
- Candidates assessed for appropriate level during interview process, with offers aligned to that level
Lab profile
About Tenstorrent
Builds high-performance RISC-V CPUs and AI accelerators with full-stack software for efficient AI computing.
What they build
- AI accelerators
- RISC-V CPUs
- AI software and compilers
Known for
- Custom RISC-V CPU development from scratch
- Full-stack AI hardware and software
- Performance, ease of use and cost efficiency
Key facts
- Founded in 2016
- Headquartered in Toronto, Canada
- Backed by Samsung and Hyundai Motor Group