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Normal Computing

Develops probabilistic AI for enterprise applications

Simulator & Debug Tools Lead

Hardware Validation & TestingUpdated on Nov 13
Full-time$200k - $300k /yrIn-person

About the Job

Requirements

  • Experience building or leading development on hardware simulators, cycle-accurate or functional, for ASICs or novel compute architectures.
  • Experience building debuggers, tracers, or profilers that other engineers adopted.
  • Systems and compiler context sufficient to simulate both the software stack running on the hardware and the hardware itself.
  • Comfort working with evolving hardware and evolving the simulator alongside it.
  • Fluency in C++ or Rust for simulator performance, and familiarity with Python for tooling.

Responsibilities

  • Own the architecture and roadmap of the hardware simulator, including its accuracy, performance, and coverage of new hardware features as they are introduced.
  • Ensure the simulator's behavior, state, and memory semantics are trustworthy enough for compiler and runtime engineers to use.
  • Build debuggers, tracers, and profilers that help engineers find and fix bugs.
  • Partner with Design Verification and bring-up teams to correlate the simulator with RTL, FPGA prototypes, and eventually silicon, and resolve discrepancies.
  • Build simulator benchmarks and traces from LLM inference workloads to measure fidelity against the chip's target workloads.
  • Decide how to allocate investment among simulator fidelity, simulator speed, and tooling, and explain tradeoffs to compiler and hardware teams.

Desired Qualifications

  • Experience with in-memory compute or other non-von-Neumann architectures.
  • Experience building simulators that directly informed architectural or compiler decisions beyond post-hoc validation.
  • Experience with open-source simulation, tracing, or hardware-tooling communities.
  • Background spanning both pre-silicon simulation and post-silicon bring-up.

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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