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Normal Computing

Develops probabilistic AI for enterprise applications

Head of Silicon Product Engineering

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeNo salary listed

About the Job

Requirements

  • At least 15 years of experience in semiconductor product/test engineering, with direct ownership of silicon from NPI through high-volume manufacturing.
  • Proven experience selecting and managing OSAT and foundry partners, including cost, quality, and yield negotiations.
  • Deep hands-on background in packaging, ATE, and post-silicon bring-up and validation.
  • Experience with production test and screening methodology for complex, high-reliability products.
  • A track record of building and scaling engineering teams from early stage.
  • Strong cross-functional fluency with design, architecture, and supply chain organizations.
  • A Bachelor's or Master's degree in Electrical Engineering or a related field.

Responsibilities

  • Own end-to-end bring-up, characterization, validation, and debug across multiple silicon generations.
  • Define and drive packaging and test strategy, including ATE program development, test coverage, and test condition optimization for yield, quality, and performance.
  • Select, qualify, and manage OSAT and test-house partners, owning the relationship through NPI and into high-volume manufacturing, including cost, quality, and yield negotiations.
  • Lead yield learning and qualification efforts from early silicon through production ramp, including root-cause analysis of systematic and random failures.
  • Own production calibration and screening methodology for memory products, ensuring performance and reliability targets are met at volume.
  • Build and lead a high-performing silicon product engineering organization from the ground up, including hiring, process, and tooling.
  • Partner closely with design, architecture, and supply chain teams to ensure designs are producible, testable, and optimized for cost and yield before they become expensive to change.
  • Build the data analysis practices needed to catch failure mechanisms early, using characterization and manufacturing data from wafer acceptance testing, sort, package, and system-level test.

Desired Qualifications

  • Experience bringing up test and qualification for a new or unconventional silicon architecture, not just a new generation of a familiar one.
  • Experience with memory-adjacent product engineering, such as DRAM, HBM, or custom memory modules.
  • Experience at an AI or high-performance compute startup where design, verification, and product engineering worked in tight iteration cycles.
  • Comfort operating in an environment where the test methodology is still being invented alongside the hardware.

About the Company

Normal Computing

Develops probabilistic AI for enterprise applications

Normal Computing builds AI systems for large, mission-critical workloads and provides generative AI tailored for enterprises. It uses Probabilistic AI, which uses statistical analysis to predict outcomes, giving firms more control over reliability, adaptability, and auditability. The company differentiates itself through leadership from Google Brain, Palantir, and X, and by focusing on risk-aware, enterprise-grade AI for industries with strict risk constraints. Its goal is to help Fortune 500 companies and government agencies deploy AI in critical operations with strong reliability, clear audit trails, and manageable risk.

Company size
51-200
Company stage
Early VC
Total funding
$133M
Headquarters
New York City, New York
Founded
2022

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