Etched

Physical Design Engineer

Etched, San Jose

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About Etched
Etched is building AI chips that are hard-coded for individual model architectures. Our first product (Sohu) only supports transformers, but has an order of magnitude more throughput and lower latency than a B200. With Etched ASICs, you can build products that would be impossible with GPUs, like real-time video generation models and extremely deep chain-of-thought reasoning.
Physical Design Engineer
Etched is looking for exceptional PD engineers to join our team. The candidate will be responsible for working with 3rd party design services to implement and verify physical designs, and will help Etched as we work to improve iteration speed on physical design.
Representative Projects

Supervise the outsourcing of physical design to a 3rd party service
Deeply understand what is involved in physical design
Running Physical Design flows to close blocks, support ASIC infrastructure, automate Physical Design flows, improve CAD infrastructure
Drive dashboards that show the convergence of projects related to Physical Design
Optimize tool flows, working with EDA vendors to incorporate the latest features
Accountable for block level closure

Requirements

2+ years of previous experience with PD
Tools, flow, and design methodology from RTL synthesis to GDSII sign-off
Experience with back-end design and timing closure on 3nm-7nm
Experience with UPF-based low power design methodology, power verification, synthesis, scan insertion/ATPG, formal verification, floorplanning, placement, CTS, routing, IR drop, and EM/antenna analysis
Deeply creative and able to think from first principles

Desired Qualifications

Familiarity with transformer models and machine learning.
Familiarity with OpenROAD and other automated RTL-to-GDSII flows
Ability to program with Python or another scripting language.

We encourage you to apply even if you do not believe you meet every single qualification.
How We’re Different
Etched believes in the Bitter Lesson. We think most of the progress in the AI field has come from using more FLOPs to train and run models, and the best way to get more FLOPs is to build model-specific hardware. Larger and larger training runs encourage companies to consolidate around fewer model architectures, which creates a market for single-model ASICs.
We are a fully in-person team in West San Jose, and greatly value engineering skills. We do not have boundaries between engineering and research, and we expect all of our technical staff to contribute to both as needed.
Benefits

Full medical, dental, and vision packages, with generous premium coverage
Housing subsidy of $2,000/month for those living within walking distance of the office
Daily lunch and dinner in our office
Relocation support for those moving to West San Jose

Compensation Range

$150,000 - $275,000

Seniority level

Seniority level
Entry level

Employment type

Employment type
Full-time

Job function

Job function
Engineering and Information Technology
Industries
Computer Hardware Manufacturing

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