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14 часов назад

Lead DFT Engineer (Edge Computing)

Формат работы
remote (только India)
Тип работы
fulltime
Грейд
lead
Английский
b2
Страна
India
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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TL;DR
Lead DFT Engineer (Edge Computing) (AI Hardware): Developing end-to-end DFT architectures and test strategies for high-performance edge-computing SoCs with an accent on scan compression, MBIST, boundary scan, and low-power multi-voltage designs. Focus on implementing ATPG and BIST flows, validating silicon on ATE, and solving reliability and manufacturability challenges at advanced FinFET nodes.

Location: Bangalore, India

Company

hirify.global develops advanced AI hardware and software systems for edge-to-cloud computing, based on in-memory computing technology for high-efficiency and high-density processing.

What you will do

  • Define and implement end-to-end DFT architectures for complex SoCs, including hierarchical DFT, scan compression, boundary scan, and MBIST.
  • Develop in-system test and power-on self-test strategies for reliable operation in remote edge data centers.
  • Oversee scan insertion, ATPG for stuck-at, transition, and path-delay faults, and memory and logic BIST implementation.
  • Collaborate with Design, Physical Design, and Yield teams to maximize test coverage while minimizing area, power, and timing impact.
  • Lead post-silicon bring-up and debugging on ATE, root-causing silicon failures and optimizing test time.

Requirements

  • 12+ years of DFT experience, including at least 2 years in a leadership or principal role.
  • Expertise with Synopsys TestMAX, Siemens/Mentor Tessent, or Cadence Modus.
  • Deep experience with MBIST and repair, SCAN, IJTAG (IEEE 1687), and boundary scan (IEEE 1149.1/6).
  • Proven experience with 7nm, 5nm, or smaller FinFET nodes.
  • Experience managing DFT for multi-voltage and power-gated designs.

Culture & Benefits

  • Work on next-generation AI hardware and software for power- and space-constrained edge applications.
  • Contribute to silicon development led by experienced semiconductor and AI systems technologists.
  • Focus on high compute efficiency, manufacturability, reliability, and edge deployment.

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