韩国前调工程师

Normal Computing builds silicon that turns thermal noise from an obstacle into a computational resource. Conventional chips spend most of their energy forcing determinism onto physics; ours compute with it. Stochastic, in-memory, asynchronous: the result is 10-100× more AI inference per dollar, per watt.

Willing and able to work on-site in Korea for the duration of the deployment. Deep hardware experience paired with recent, hands-on AI experience. Great at problem-solving and tracking down issues wherever they are in the stack. Strong software engineering fundamentals: proficient in Python, comfortable in production codebases, distributed-systems literate. Hands-on experience with the modern ML stack: prompt engineering, fine-tuning, evals, RAG, agentic patterns, model deployment. Willingness and ability to go deep on semiconductor design and verification workflows, including memory. Calm in ambiguity: you make good decisions with incomplete information, and you know when to act and when to ask. Comfortable with travel when needed.

Offers Equity, Competitive and equitable compensation based on role, skills, and experience. Salary ranges are guidelines, with final compensation varying by role, experience, and location and reviewed regularly for fairness.

Normal Computing builds silicon that turns thermal noise from an obstacle into a computational resource. Conventional chips spend most of their energy forcing determinism onto physics; ours compute with it. Stochastic, in-memory, asynchronous: the result is 10-100× more AI inference per dollar, per watt.