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About the Role

Our EDA tool accelerates the design and verification of silicon by integrating with the engineer's workflow to assist with design, verification, and debugging. This role focuses on manufacturing synthetic training data with programmatic ground truth, mining agent runs for high-quality trajectories, and negotiating access to real customer data to improve AI agent performance.

Responsibilities

• Make models better at hardware design, verification, and EDA workflows.
• Own the data flywheel from agent runs, including rejection sampling, distillation, and mining eval-passing trajectories.
• Identify, evaluate, and acquire datasets relevant to hardware design, verification, and EDA workflows.
• Define rubrics, curate golden reference examples, and assess data quality with verification engineers.
• Operate data ingestion pipelines, monitor for quality regressions and coverage gaps, and maintain a structured catalog of data sources, acquisition strategies, and lineage.
• Negotiate access to customer data on-prem and federated, handle redaction and IP constraints, and build external replicas of customer environments.
• Manage engineers across synthetic data, verification SME curation, data infrastructure, and forward-deployed data engineering as the Data team scales.

Requirements

• Built or used a data flywheel: model outputs, curated, into the next training round.
• Approach data acquisition as an engineering problem: systematic, measurable, and outcome-driven.
• Shipped a synthetic-data or training-data pipeline that produced a measurable downstream model improvement.
• Can evaluate data quality independently, spotting noise, bias, and gaps.
• Comfortable working across multiple technical roles and synthesizing feedback from domain experts, ML engineers, and pipeline engineers.
• Organized and documentation-minded: track provenance, ownership, and lineage as a matter of habit.

Skills

• SystemVerilog
• Verilog
• UVM
• Automated data collection
• Web scraping
• Corpus curation at scale
• Code-model or agent training-data pipelines

Location

• New York
• Silicon Valley
• London
• Copenhagen
• Seoul

Work Type

• Full-time

Experience Level

• All seniority

About the Company

• Normal Computing builds silicon that turns thermal noise from an obstacle into a computational resource, resulting in 10-100x more AI inference per dollar, per watt.
• They co-design the full stack: AI-native EDA systems and advanced ASICs.
• Backed by $85M+ from leading deep-tech investors and built by experts from the labs that built modern computing.
• Normal works as one team across New York, Silicon Valley, London, Copenhagen, and Seoul.
• They hire people who want the hardest version of their craft, across every discipline, at every seniority.

Equal Opportunity

• 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.
• 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.
• 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.