Director of AI/ML Engineering (EDA & Semiconductor Design)

Company Description

Renesas is one of the top global semiconductor companies in the world. We strive to develop a safer, healthier, greener, and smarter world, and our goal is to make every endpoint intelligent by offering product solutions in the automotive, industrial, infrastructure and IoT markets. Our robust product portfolio includes world-leading MCUs, SoCs, analog and power products, plus Winning Combination solutions that curate these complementary products. We are a key supplier to the world’s leading manufacturers of electronics you rely on every day; you may not see our products, but they are all around you.

Renesas employs roughly 21,000 people in more than 30 countries worldwide. As a global team, our employees actively embody the Renesas Culture, our guiding principles based on five key elements: Transparent, Agile, Global, Innovative, and Entrepreneurial. Renesas believes in, and has a commitment to, diversity and inclusion, with initiatives and a leadership team dedicated to its resources and values. At Renesas, we want to build a sustainable future where technology helps make our lives easier. Join us and build your future by being part of what’s next in electronics and the world.

Job Description

In this role, you will lead the definition and execution of AI/ML-driven initiatives, drive adoption of ML/AI across frontend and backend design and development flows across the company, enable next-generation intelligent design automation capabilities, and collaborate with cross-functional leaders to integrate AI into engineering productivity, automation, and decision-making processes.

Job Responsibilities

• Define and own the AI/ML strategy for Engineering group’s software and design flows

• Lead the transformation of semiconductor design workflows by deploying AI-driven (agentic) solutions across Frontend (modelling, synthesis, optimization) and Backend (place-and-route, timing closure, physical optimization)

• Drive end-to-end integration of AI into engineering toolchains

- Establish scalable frameworks for:

• Data collection, labelling, and pipeline management