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Normal Computing is an applied AI company building foundational hardware and software for the semiconductor industry and critical AI infrastructure. As an early-career Product Manager, you will partner with the Product Lead and engineering teams to develop the AI systems and autoresearch platform that enables the ASIC team to tapeout unconventional, physics-based chip architectures.
You will help rethink the chip design system from the ground up, automating research workflows: exploring design spaces, generating candidate architectures, evaluating them at appropriate fidelity levels, and feeding learnings from hardware labs and deployed silicon back into next-generation chip development. Domains include RTL optimization, design verification, and continual learning from experiment results.
On a typical day, you might benchmark novel architectures with chip architects, observe verification debug sessions and propose automation opportunities, scope requirements for custom EDA tools, or prototype experiment dashboards. This is a hands-on building role: you will write specs, run experiments, and use coding agents to prototype and land fixes yourself. The team values rapid prototyping over lengthy documentation.
Key responsibilities:
- Investigate where the ASIC team's time is spent and decide what AI tooling to build, then own accountability for adoption and usage.
- Write requirements documents and user journeys that engineering builds from; prototype when it communicates faster than documentation.
- Shepherd prototypes into production-ready tools the ASIC team can rely on.
- Contribute directly to the codebase using coding agents, open PRs for bug fixes and UI improvements, learn from code reviews, and develop judgment about which changes to own.
No semiconductor background is required. In your first few months, success means understanding how the team works, asking questions that advance design discussions, and earning trust through reliable delivery.
REQUIREMENTS:
- Degree in CS, EE, physics, math, or equivalent self-taught background.
- 1–3 years of experience in product management, engineering, research, technical program management, or related technical role.
- Demonstrated ability to take an idea from conception to reality.
- Fluency with coding agents (Claude Code, Codex, Cursor, or similar) as a regular part of your workflow.
- Experience building or evaluating LLM-powered products.
- Clear communication in both speaking and writing.
- Comfort with ambiguity; ability to frame underspecified problems and propose solutions.
- Interest in chip design.
BONUS:
- Coursework, research, or internship in chip architectures, digital design, verification, or hardware performance modeling.
- SystemVerilog exposure.
- Familiarity with LLM inference mechanisms.
