Design Verification Engineer

ABOUT NORMAL COMPUTING Normal Computing builds silicon that turns thermal noise from an obstacle into a computational resource. Conventional chips spend most of their energy forcing determinism onto physics; ours compute with it. Stochastic, in-memory, asynchronous: the result is 10-100× more AI inference per dollar, per watt. We co-design the full stack: AI-native EDA systems in production with the world's largest semiconductor companies, and the advanced ASICs they make possible. Backed by $85M+ from the world's leading deep-tech investors and built by scientists, engineers, and operators from the labs that built modern computing. Normal works as one team across New York, Silicon Valley, London, Copenhagen, and Seoul. We hire people who want the hardest version of their craft, across every discipline, at every seniority. THE ROLE - AI Product Refinement: Review AI-generated collateral to help shape product strategy and refine AI outputs in collaboration with the ML team. - Thermodynamic ASIC Verification: Provide design verification for internal hardware projects - Tool Usability: Set up and evaluate EDA tools, ensuring internal tool usability and effective deployment on shared computing resources. - Testbench Development: Verification collateral development: create testbench environments, assertions, and coverage, from design documents, to support product development, functional coverage, and coverage closure. - Dataset Annotation: Curate and annotate datasets to make it easier to associate specific parts of a chip specification with specific test cases. - Quality Control: Establish rigorous quality criteria for verification data and implement continuous refinement processes. - Automated QA: Implement data augmentation methods and automated quality assurance checks to ensure high-fidelity data for ML training. - Synthetic Data Creation: Generate synthetic data using AI-based methods to supplement real datasets. - ML Collaboration: Collaborate with ML teams to ens