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Hardware Engineer, Design Verification

Role overview

Qualifications

  • 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), plus 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

  • AI product refinement: Review AI-generated collateral to shape product strategy and refine AI outputs in collaboration with the ML team
  • Thermodynamic ASIC verification: Provide end-to-end design verification for internal hardware projects (Physics-inspired ASICs)
  • Tooling and data pipeline: Set up and evaluate EDA tools, build automated pipelines to annotate test data and link it to chip specifications, and ensure tool usability on shared compute resources
  • Testbench and data quality: Develop testbenches, create assertions and coverage from design documents, curate datasets with annotations, and implement automated QA and synthetic data generation to support ML training

About the company

Normal Computing logo

Normal Computing

Information Technology & Services

At Normal, our mission is to make AI universally scalable and useful. AI has been subject to technological limitations such as unpredictable factual errors in generative AI or lack of auditability as black-box models. We believe that AI can unlock transformative value in enterprise applications by reasoning reliably, autonomously, and understanding its own limits. Our products enable AI deployment in high-stakes enterprise applications. Unlike other surface-level approaches, our approach involves redesigning AI systems from the ground up. Normal's AI application development platform is powered by novel full-stack probabilistic machine learning infrastructure driven by thermodynamic physics. Normal was founded by former engineers from Google Brain, Alphabet X, and Palantir. We engage with leading institutions across various industries, including services, manufacturing, and the public sector.

Company details

Company typeScaleup
IndustryInformation Technology & Services
Company size11 - 50

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Job description

Normal Computing | Incredible Opportunities

The Normal Team builds foundational software and hardware that help move technology forward - supporting the semiconductor industry, critical AI infrastructure, and the broader systems that power our world. We work as one team across New York, San Francisco, Copenhagen, Seoul, and London.

Your Role in Our Mission:

You will bring your expertise in the end-to-end design verification flow to support our Verification AI team. This is a hybrid verification and product-shaping role. You will verify internal hardware (Physics inspired ASICs) while simultaneously reviewing the collateral generated by our AI to help refine product strategy and tool usability. You will act as the bridge between raw verification data and our Machine Learning models, ensuring our AI learns from high-quality, curated, and synthesized data.

Responsibilities:

  • 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.

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Marcus Rivera

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