Hardware Engineer - Design Verification

21h21 hours ago

Normal Computing

Seoul, KR · Full-time · $140,000 – $180,000

About this role

Normal Computing builds foundational software and hardware that move technology forward, supporting the semiconductor industry, critical AI infrastructure, and broader systems. As part of the Verification AI team, you will bring end-to-end design verification expertise to a hybrid role combining verification and product shaping.

You will verify internal Physics inspired ASICs while reviewing AI-generated collateral to refine product strategy and tool usability. Day-to-day work involves setting up EDA tools, developing testbench environments, annotating datasets, and generating synthetic data to challenge verification models.

You act as the bridge between raw verification data and Machine Learning models, ensuring the AI learns from high-quality curated data. The team operates across New York, San Francisco, Copenhagen, Seoul, and London, fostering a collaborative global environment.

This role offers a unique opportunity to shape AI product strategy by directly influencing how verification data is synthesized and fed into ML training pipelines. Your contributions will help refine automated quality assurance and advance the frontier of AI-driven hardware verification.

Requirements

5+ years of experience in Digital Verification at a major semiconductor or EDA tool company.
Advanced proficiency in SystemVerilog, UVM methodology, and EDA verification tools (vManager, Xcelium, Jasper).
Proficiency and application of Python or Perl scripting.
Proven expertise in end-to-end design verification, including test plan creation, stimulus generation, and feature extraction.
Excellent written and spoken communication skills.

Responsibilities

Review AI-generated collateral to shape product strategy and refine AI outputs in collaboration with the ML team.
Provide design verification for internal Thermodynamic ASIC hardware projects.
Create testbench environments, assertions, and coverage from design documents to support product development and coverage closure.
Curate and annotate datasets to associate specific parts of chip specifications with test cases.
Generate synthetic data using AI-based methods to supplement real datasets.
Build automated pipelines to annotate test data and link it explicitly to chip specifications.
Automate document parsing (e.g., datasheets, protocol specifications) for contextual tagging and traceability.
Establish rigorous quality criteria for verification data and implement continuous refinement processes.

Benefits

Opportunity to bridge verification and AI/ML product development, shaping the future of AI-driven hardware verification.
Collaborate with global teams across New York, San Francisco, Copenhagen, Seoul, and London.
Commitment to an inclusive environment and accessibility accommodations for all employees.