Research Intern - AI-Driven SoC Design Loop

SK hynix memory solutions America Inc.

San Jose (CA)

Presencial

USD 48 000 - 62 000

Tempo integral

Há 3 dias
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Resumo da oferta

SK hynix memory solutions America Inc. is seeking a research intern in loop engineering in San Jose. You will own a scoped research question, build or extend the loop, run experiments, and write up results for design automation.

The role focuses on AI-assisted hardware/software co-design flows and practical application to SoC problems. Responsibilities include structuring the loop, implementing with Chisel and XLS, comparing loop designs, ensuring reproducibility, and delivering a rerunnable

Qualificações

  • Fluency in Python and comfort reading and modifying an existing codebase.
  • Ability to pose a small research question and document changes.
  • Experience with loop engineering, computer architecture, digital design, or EDA is a plus.

Responsabilidades

  • Study how a design loop should be structured and how steps feed each other.
  • Implement the loop with tools such as Chisel and XLS and run simulations.
  • Apply loop to an SoC problem like microarchitectural exploration or RTL verification.
  • Compare loop designs on quality, search cost, reproducibility, and failure diagnosis.
  • Make the loop rerunnable with clear interfaces, cached results, and regression reports.

Conhecimentos

Python
Codebase reading
Research question framing

Formação académica

Bachelors/Masters/PhD in EE/CE/CS

Ferramentas

Chisel
XLS

Descrição da oferta de emprego

SK hynix memory solutions America Inc. is seeking a research intern in loop engineering in San Jose. You will own a scoped research question, build or extend the loop, run experiments, and write up results for design automation.

The role focuses on AI-assisted hardware/software co-design flows and practical application to SoC problems. Responsibilities include structuring the loop, implementing with Chisel and XLS, comparing loop designs, ensuring reproducibility, and delivering a rerunnable

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