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Role description

Physical Design - CAD Lead

Efficient Computer logoEfficient Computer
SenioritySenior
Salary$180,000–$260,000
LocationSan Francisco, CA · Pittsburgh, PA · Austin, TX
Posted2/20/2026
Engineering

Efficient Computer is rethinking computing from the ground up to solve one of AI's biggest challenges: energy. Our Fabric architecture delivers a 10–100x improvement in energy efficiency for general-purpose computation, including AI, while supporting familiar programming languages and software frameworks—unlocking new possibilities for autonomous machines, intelligent infrastructure, wearables, and space systems. With our first processor, Electron E1, now shipping in volume and more than $97 million in Series B financing recently announced, we're accelerating customer deployments and scaling our architecture to data center performance. Join us to build the hardware and software that bring intelligence wherever it's needed and help shape the next generation of computing.

 Efficient is seeking a CAD Lead - PD flows/infrastructure  to join our growing team. The ideal CAD Lead would have worked on significant portion of the full gamut of Physical Design flows and flow infrastructure (flowtracer etc).  This role is in a newly formed hardware engineering group and is the seed hire for this discipline. You will get to setup CAD flows and infra from scratch and influence and shape this aspect in the future.

This is a unique opportunity to get in at the early stages of a hardware engineering organization and have influence on our products as we move from initial stages of product development to market release and scaled volume production. Join our team and help us shape the future of computing at the edge and beyond!

Key Responsibilities

  • Drive and develop PD flows, methodology for state of the art finfet and multi patterning  based technologies from scratch in Cadence Tempus or Synopsys Primetime.
  • Help develop repeatable, predictable , design and process agnostic PD flows.
  • Develop state of the art flow infrastructure to enable consistent and rapid design under tight schedule constraints for multiple product lines in the energy efficient edge AI computing market.
  • Work closely with PD team leads to propose and develop end to end build and signoff flows.
  • Build regression frameworks for ensuring high quality flows and achieve hardware engineering vision of spending 90% or more time on actual design tasks and NOT wrestling with tools.
  • Develop collateral quality checking utils to ensure high design efficiency.
  • Develop and deploy a unified environment for specifying all collaterals (stdcell, memory, PDK, hardips…)  and all flow dependencies (cycle time, PVTRC corners, per flow design and process dependent configuration).
  • Work with 3rd party vendor resources and coordinate their work.
  • Continuously work on improving flow consistency and efficiency in the context of multiple product lines.

Required Qualifications

  • Master's degree in Electrical Engineering with 5+ years of industry experience or PhD in Electrical Engineering with 3+ years of industry experience
  • Strong python other scripting programming skills.
  • Experience in developing workflow orchestration infrastructure or tools for hardware development (Airflow, flowtracer etc)
  • Familiarity with kubernetes and containerization
  • Experience implementing regression frameworks
  • SQL or other database proficiency (MongoDB ..)
  • Intimate knowledge of hardware design workflows for Physical Design and RTL/DV.
  • Excellent scripting skills in TCL, shell and python.

Desired Qualifications & Experience Requirements

  • Experience in full chip RTL/DV and PD flows.
  • Knowledge of circuit design, device physics, deep sub-micron technology, and SOI technology and its implications to physical design
  • Proficiency with industry-grade physical design flow and hands-on building CAD flow infrastructure for PD engineers.
  • Definition of design constraints for static timing analysis (synthesis, pre/post‑cts, sign‑off) and corners/voltage definitions.
  • Experience in integrating analog or mixed-signal macro on top-level design.
  • Experience in verifying IP collaterals.

We offer a competitive base salary for this role, generally ranging from $180,000 to $260,000, plus a 10% annual bonus, meaningful equity, and comprehensive benefits. Final compensation will depend on experience, level, and location, with flexibility for the right candidate.

Why Join Efficient?

Build what's next. At Efficient, you'll tackle big challenges with room to take ownership and make an impact. We back you with competitive pay, equity, a 401(k) match, company-paid benefits, paid parental leave, and flexibility—plus opportunities to grow your skills and career as we scale.

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Company info

Efficient Computer logo

Efficient Computer

The most energy-efficient general purpose processors ever made.

Efficient is building the world’s most energy-efficient general-purpose processor by combining ultra-efficient hardware with an intuitive, developer-friendly compiler and software stack that unlocks 10–100× efficiency gains across every part of an application, including AI. Efficient was founded in 2022 to commercialize a breakthrough in efficient computation developed over nearly a decade by a team of world-leading computer architects. Efficient's world-class team has produced two silicon implementations of the Fabric architecture: the Electron E0, a prototype system-on-chip, and the Electron E1, the first silicon product. With Efficient's cutting-edge effcc Compiler and software stack, the Electron E1 processor has been delivered to customers as of mid-2025, ramping to large-scale volume and distribution in 2026. Efficient already has customer traction in areas such as physical AI for infrastructure and automation, space and defense, automotive, and consumer products. Efficient's tec

Private companySeries BRecently raisedIn the news
Founded2022
HQ
Pittsburgh, United States
Size11–50 employees
IndustryComputer Hardware Manufacturing
Latest fundingSeries B · Sep 29, 2026
Investors
TQ Ventures
Tech stackkandji, jenkins, trackit, redis, buildkite, macos, microsoft-forefront, aws-iot, bazel, runai, elearning-lms, workspace, slack, cplusplus, cuda, pytorch, cmake, jira, parse, nodejs
News
  • edgeAI Selects Efficient Computer's Electron E1 for Next-Generation Physical AI Products
  • Efficient Computer’s Electron E1 processor adopted by edgeAI
  • edgeAI Selects Efficient Computer's Electron E1 for Next-Generation Physical AI Products

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