Design Verification Engineer – AI-Driven Verification Solutions

About the Role:
We are seeking an experienced Design Verification (DV) Engineer to collaborate with our AI engineering and product teams in developing next-generation AI-driven verification tools. Our product leverages artificial intelligence to accelerate silicon verification — helping chip teams reach tape-out faster and with higher confidence.
In this role, you will help generate DV collaterals, assist in data labeling and model training, and provide valuable product insight to improve the accuracy and efficiency of our AI verification solutions. This is a unique opportunity to combine deep semiconductor verification expertise with the emerging field of AI-assisted EDA innovation.

Key Responsibilities:
Work closely with AI engineers and product managers to create, refine, and annotate DV datasets for AI model training.
Generate DV collateral, including testbenches, assertions, coverage data, and regression results, to support AI learning workflows.
Provide domain expertise and feedback on how AI can augment the verification process and improve engineer productivity.
Collaborate with internal and external teams to validate and evaluate AI-assisted verification features.
Contribute to the design and evolution of AI-powered workflows for chip verification.
Communicate technical findings and product insights clearly to engineering and product leadership.

Required Qualifications:
5+ years of experience in Design Verification within a semiconductor or EDA company.
Strong knowledge of SystemVerilog, UVM, and functional verification methodologies.
Experience in memory chip verification or verification of memory-related subsystems.
Understanding of how AI and machine learning can be applied to automate or enhance DV workflows.
Ability to work during partial US East Coast hours to collaborate effectively with cross-functional teams.
Excellent communication skills and ability to explain complex technical ideas clearly.

Preferred Qualifications:
Experience generating or curating datasets for AI or ML applications.
Familiarity with AI/ML tools, data labeling processes, or model training pipelines.
Prior experience collaborating with software, data science, or AI product teams.
Scripting skills (Python, Perl, TCL, or similar) for data automation or analysis.
Passion for innovation at the intersection of semiconductors, AI, and verification technology.