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Normal Computing

Develops probabilistic AI for enterprise applications

Thermodynamic Hardware Resident

Hardware EngineeringConfirmed live in the last 24 hours
Internship$72.12 /hrIn-person

About the Job

Requirements

  • Currently pursuing or recently completed a graduate degree (MS or PhD, or equivalent research experience) in physics, electrical engineering, computer engineering, computer science, applied math, or a related field, with a focus on hardware, device physics, stochastic or analog computing, or machine learning systems.
  • Comfort moving between the physics of noise and analog devices, circuit- and architecture-level tradeoffs, and algorithms and workloads for the hardware.
  • Some exposure to large-model inference concepts, including attention mechanisms, KV caching, and long-context decoding.
  • Strong Python skills and comfort with, or eagerness to learn, a lower-level systems language such as C++ or Rust.
  • First-principles reasoning about novel computational substrates and curiosity about unconventional computing.
  • Strong written and verbal communication skills.
  • A bias toward ownership and self-direction in an ambiguous, fast-moving startup environment.

Responsibilities

  • Work hands-on with thermodynamic hardware by helping design, simulate, characterize, or evaluate hardware incorporating noise, analog dynamics, and in-memory computation.
  • Design numerical methods and algorithms that exploit thermal noise and analog dynamics rather than techniques designed for conventional digital hardware.
  • Partner with researchers and hardware engineers to scope, conduct, and iterate on an original technical investigation, from device- or circuit-level physics through algorithms and workloads mapped to thermodynamic computing.
  • Build tests and benchmarks to measure algorithmic performance on real hardware and in simulation, and feed model-workload findings into hardware design decisions.
  • Co-author a research paper for submission to a relevant venue.
  • Present research at the residency colloquium to the broader Normal Computing research community.
  • Work directly with founders, senior researchers, and engineers in a lean, fast-moving environment.

Desired Qualifications

  • Hands-on experience with simulation, experimentation, or hardware characterization, such as SPICE, PyTorch, FPGA, or ASIC tooling.
  • Prior experience writing up research in papers, theses, or technical reports.
  • Experience presenting technical work to a live audience.

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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