Normal Computing

Normal Computing

Research Engineer, Algorithms

New York City

Sponsorship not specified$10k-$100kDetected 3 days ago
PythonFull-Stack DevelopmentAlgorithmsMachine LearningNLPAccessibilityElectrical EngineeringResearch

About the role

  • The core challenge is not adapting standard GPU kernels to a new chip.
  • It is rethinking how operations like attention, memory access, and long-context decoding behave when the underlying substrate uses stochastic analog computation in memory rather than conventional digital logic.
  • Normal's ASICs run the heaviest operations of large model inference inside memory itself.

Responsibilities

  • understand what transformer and diffusion workloads are well-suited to stochastic analog execution, design numerical methods that map onto the hardware's physical dynamics, and validate them against real silicon or high-fidelity simulation.
  • This is a co-design role.
  • The hardware and the algorithms are developed in parallel, which means you will influence architectural decisions, not just implement against a fixed specification.
  • Develop algorithms for transformer inference workloads running on stochastic analog processing-with-memory hardware.
  • Design numerical methods that exploit thermal noise and analog dynamics rather than working around them.
  • Translate insights about model workloads into constraints and opportunities for hardware design.
  • You will develop the computational methods that make AI inference run efficiently on Normal's thermodynamic hardware.
  • Algorithm Development: Develop algorithms for transformer inference workloads running on stochastic analog processing-with-memory hardware.

Requirements

  • Experience with inference optimization: quantization, sparsity, kernel fusion, or memory-efficient attention
  • Familiarity with stochastic systems, probabilistic methods, numerical analysis, or analog computation
  • Collaborative instinct and ability to work across hardware, architecture, and software teams

Skills

  • Experience implementing algorithms close to hardware, not just in high-level frameworks
  • Strong programming skills in Python and at least one systems language

Compensation

  • $10k-$100k

Benefits

  • PhD in machine learning, applied mathematics, physics, electrical engineering, or a related field

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.
  • Accessibility Accommodations

This listing is sourced directly from Normal Computing's careers page and normalized into a canonical job model.