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 ensure synthetic data effectively challenges verification models.

• Pipeline Automation: Build automated pipelines to annotate test data and link it explicitly to chip specifications.

• Document Parsing: Automate document parsing (e.g., datasheets, protocol specifications) for contextual tagging and traceability.
  

What Makes You A Great Fit

• Experience: 5+ years of experience in Digital Verification at a major semiconductor or EDA tool company.

• Technical Stack: Advanced proficiency in SystemVerilog, UVM methodology, EDA verification tools (vManager, Xcelium, Jasper), and proficiency and application of Python or Perl scripting.

• Domain Knowledge: Proven expertise in end-to-end design verification, including test plan creation, stimulus generation, and feature extraction.

• Communication: Excellent written and spoken communication skills.

Equal Employment Opportunity Statement

Normal Computing is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other legally protected status.

Accessibility Accommodations

Normal Computing is committed to providing reasonable accommodations to individuals with disabilities. If you need assistance or an accommodation due to a disability, please let us know at accommodations@normalcomputing.com.

Privacy Notice

By submitting your application, you agree that Normal Computing may collect, use, and store your personal information for employment-related purposes in accordance with our Privacy Policy.