Drimva

Unconventional AI

AI Silicon, DFT Engineer

Mountain View, CA I Remote +2 · Remote · Full-time · Posted Oct 1, 2026

Location
Mountain View, CA I Remote
Mountain View
Remote
Experience
10+ years of industry experience in digital DFT and test architecture; successful tapeouts on modern process nodes, with 7nm, 5nm, or newer preferred.
Education
B.S. or M.S. in Electrical Engineering, Computer Engineering, or a related field.

About the job

Leads design-for-test architecture and implementation for an AI computing platform, enabling reliable testing of digital logic, mixed-signal blocks, and stacked-die designs.

What you'll do

  • Implement scan compression, MBIST, JTAG/boundary scan, hierarchical DFT, and test integration for SoC designs.
  • Develop and sign off test strategies, including ATPG, fault simulation, timing closure, and test coverage and yield optimization.
  • Collaborate with foundries, architects, and partners on defect analysis, advanced packaging test, analog macro testability, and design-flow automation.

What they ask for

  • Deep expertise in scan compression, MBIST generation, fault modeling, and ATPG.
  • Expertise in STA and timing closure for shift and capture test modes; understanding of advanced-node physical design challenges.
  • Expert-level mastery of standard EDA CAD tools and strong scripting skills in Tcl, Python, or Perl.
  • Excellent written and verbal communication skills, including experience managing external vendor or design-house deliverables.

Nice to have

  • Hands-on experience with die-to-die test, chiplet testing, or 3D-IC DFT; experience testing ML accelerators or large-scale systolic arrays.
  • Experience integrating custom analog macros and complex power sequencing; familiarity with AI tools for chip design.

Tools

scan compression, MBIST, JTAG, IEEE 1838, ATPG, Static Timing Analysis (STA), Tcl, Python

AI focus

Develops testability for an AI computing platform and may evaluate AI tools to improve chip design efficiency; familiarity with AI design tools is preferred.

Model-written summary · the original posting is authoritative

First seen Oct 30, 2026 · Last verified Nov 5, 2026 (UTC)