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Unconventional AI

Analog computing substrate for energy-efficient AI

Technical Program Manager

Program ManagementConfirmed live in the last 24 hours
Full-timeMountain View, CA, USANo salary listedIn-person

About the Job

Requirements

  • At least 10 years of technical program management experience in silicon, systems, or machine-learning infrastructure.
  • Strong written and verbal communication across highly technical teams.
  • A Bachelor of Science or Master of Science degree in Computer Science, Electrical Engineering, or a related field.
  • Experience with hardware-software codesign programs, such as AI accelerators, novel compute architectures, or research silicon.

Responsibilities

  • Drive test chip programs from architecture exploration through tapeout, bring-up, and characterization, coordinating four-month tapeout cycles across silicon, hardware architecture, and systems teams.
  • Own hardware-software co-development schedules and dependencies, keeping software, compilers, and system integration workstreams synchronized with silicon decisions.
  • Build and maintain program infrastructure for rapid iteration by tracking experiments, capturing learnings, managing risk, and making tradeoffs visible.
  • Work across AI theory, system modeling, and silicon teams to turn research directions into executable program plans, understanding the learning goals for each test chip and structuring programs around them.
  • Prepare the organization for product execution by evolving program discipline from research velocity toward production readiness.

Desired Qualifications

  • Understanding of the chip development lifecycle, including architecture, RTL, tapeout, bring-up, and validation.
  • Familiarity with compiler and runtime development and system software integration.
  • Fluency with agentic tools and AI-assisted workflows to scale program management without increasing headcount or meetings.
  • Ability to work with ambiguity and build structure without imposing processes that slow teams down.
  • Technical depth to engage credibly with chip architects, compiler engineers, and machine-learning researchers.
  • A track record of shipping in fast-moving environments such as startups, research labs, or skunkworks programs.

About the Company

Unconventional AI

Analog computing substrate for energy-efficient AI

Unconventional AI designs analog AI hardware and silicon substrates that run neural networks directly in hardware. Its chips use analog circuits that mimic biological neuron dynamics to process AI workloads in the physics of silicon, reducing energy use compared with digital GPUs. It differentiates itself by pursuing an in-hardware, neuromorphic-style substrate rather than optimizing existing GPUs, supported by prominent venture funding. Its goal is to counter the AI energy bottleneck and enable scalable AI in data centers with biology-scale efficiency.

Company size
51-200
Company stage
Seed
Total funding
$475M
Headquarters
San Diego, CA
Founded
2025

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