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$31k – $57k per year (Estimated)
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In office (Paris)
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Cadence Design Systems is an American software company founded in 1988 that supplies the electronic design automation tools engineers use to design and verify integrated circuits. Its products cover digital synthesis and place-and-route, custom and analogue design, circuit simulation with the Spectre and Virtuoso families, functional verification, and increasingly system-level analysis for packaging, thermal behaviour and computational fluid dynamics. Headquartered in San Jose and listed on Nasdaq, it also licenses design intellectual property such as processor and interface blocks, and competes primarily with Synopsys and Siemens EDA.

At Cadence, we hire and develop leaders and innovators who want to make an impact on the world of technology.

At Cadence, we hire and develop leaders and innovators who want to make an impact on the world of technology.

Cadence is a pivotal leader in electronic design, building upon more than 30 years of computational software expertise. The company applies its underlying Intelligent System Design strategy to deliver software, hardware and IP that turn design concepts into reality.

Cadence customers are the world’s most innovative companies, delivering extraordinary electronic products from chips to boards to systems for the most dynamic market applications including consumer, hyperscale computing, 5G communications, automotive, aerospace industrial and health.

We are looking for an intern in Digital implementation

Title: Intern

Location: Meylan, France

Duration: 6 months

From: from February/March 2027

Internship Description

This internship explores how far a junior engineer can progress in digital implementation by relying primarily on InnoStack, Cadence’s AI-powered engineering super-agent. Starting from an RTL design, the intern will be responsible for delivering a complete RTL-to-GDSII flow and a final fabrication-ready database. The project must be carried out almost entirely through interactions with InnoStack, which will serve as the primary source of learning, guidance, methodology, script generation, and troubleshooting throughout the internship.

The intern will:

  • Learn and execute a complete Digital RTL-to-GDSII implementation flow using InnoStack as the primary guide.
  • Generate scripts, methodologies, and solutions through AI-assisted interactions.
  • Run and optimize implementation stages using Cadence tools.
  • Analyze, diagnose reports and resolve technical issues with InnoStack support.
  • Validate AI recommendations and deliver a fabrication-ready database.
  • Document best practices, effective prompts, limitations, and lessons learned throughout the project.

In parallel, the intern will maintain an InnoStack Experience Roadbook documenting effective prompts, successful and unsuccessful AI guidance, learning accelerators, limitations encountered, and recommended best practices for future users.

The final deliverables will include:

  • A complete RTL-to-GDSII implementation flow and fabrication-ready database.
  • An assessment of InnoStack’s effectiveness, strengths, limitations, and recommended methodology for guiding engineers with limited implementation experience.

This internship provides a unique opportunity to evaluate how AI can transform the way semiconductor engineers learn, execute, and master complex digital implementation flows.

Internship Requirements

  • Final-year Engineering or Master's student in Electronics, Microelectronics or a related field.
  • Basic knowledge of digital IC design, RTL, Linux, and scripting (Python/Tcl).
  • Strong interest in semiconductor design, EDA tools, and AI-assisted engineering.
  • Curious, autonomous, and eager to learn complex technical topics independently.
  • Analytical mindset with strong problem-solving and critical-thinking skills.
  • Interest in generative AI, prompt engineering, and emerging technologies.
  • Good communication, documentation, and teamwork skills.
  • Fluent in English.

Nice to Have

  • Exposure to ASIC/digital implementation flows.
  • Experience with EDA tools and AI assistants.
  • Basic knowledge of physical design concepts.
  • Personal projects in semiconductors, AI, automation, or software development.

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