Drimva

Upscale AI

Design Verification Engineer

$212K–$246K

US - Santa Clara, CA · On-site · Full-time · Posted Jul 1, 2026

Experience
10+ years of industry experience with a bachelor's degree, or 7+ years of relevant experience with a master's degree.
Education
Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field, or a Master's degree.

About the job

Verifies complex ASIC designs at block and chip levels, building verification environments and using coverage, simulation, formal methods, and AI-assisted techniques to improve design quality and efficiency.

What you'll do

  • Develop verification environments, testbenches, plans, test cases, and reusable verification components for block- and system-level designs.
  • Verify RTL using directed and constrained-random testing, assertions, formal techniques, functional coverage, and gate-level simulation; analyze coverage and debug issues.
  • Improve verification workflows and infrastructure, including applying data analytics and AI-assisted techniques to test generation, regression analysis, coverage optimization, and debugging.

What they ask for

  • Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field with 10+ years of industry experience, or a Master's degree with 7+ years of relevant experience.
  • Proven experience verifying complex ASIC designs at block and system levels.
  • Strong proficiency with SystemVerilog and the Universal Verification Methodology (UVM).
  • Experience with verification planning, functional coverage, assertion-based verification, constrained-random verification, and regression management.

Nice to have

  • Domain knowledge of Ethernet, PCIe, and switch fabric architectures.
  • Familiarity with data analytics, AI/ML-assisted verification techniques, or automation tools.

Pay

USD 212,000–246,000 per-year-salary (base salary)

Tools

SystemVerilog, Universal Verification Methodology (UVM), C, C++, Python, Ethernet, PCIe

AI focus

Applies data-driven analytics and AI-assisted techniques to test generation, regression analysis, coverage optimization, and debug productivity.

Model-written summary · the original posting is authoritative

First seen Oct 29, 2026 · Last verified Nov 4, 2026 (UTC)