Senior Software Engineer, AI/EDA & RTL Tools

Google; Lavamünd; Vor Ort; EUR 90.000 - 150.000; Vollzeit

Zusammenfassung

Google DeepMind seeks a Software Engineer to build a world-leading general-purpose learning agent and to accelerate Google's chip design through EDA tooling. The role involves designing, developing, and optimizing software for RTL generation and hardware compilation, profiling bottlenecks, and collaborating with hardware architects, compiler engineers, and ML researchers to deliver production-grade tools.

A strong software engineering foundation and the ability to tackle a broad range of

Qualifikationen

• Bachelor's degree or equivalent practical experience.
• 8 years of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript).
• 5 years of experience in software development, and with data structures/algorithms.

Aufgaben

• Design, develop, and optimize software tools to improve the quality of generated RTL and accelerate the execution of hardware compilation and EDA tools.
• Profile, identify, and resolve performance bottlenecks in software tools to speed up optimization and synthesis cycles.
• Collaborate with hardware architects, compiler engineers, and ML researchers to bridge the gap between high-level representations and highly optimized RTL.
• Develop robust, scalable automation scripts and software libraries to streamline and speed up RTL generation and optimization workflows.
• Work with product engineering teams to bring the software tools we are developing to production quality.

Kenntnisse

Software development

DS & algorithms

Multi-language programming

Ausbildung

Bachelor's degree or equivalent practical experience

Master's or PhD (preferred)

Tools

EDA tools

Jobbeschreibung

Google DeepMind seeks a Software Engineer to build a world-leading general-purpose learning agent and to accelerate Google's chip design through EDA tooling. The role involves designing, developing, and optimizing software for RTL generation and hardware compilation, profiling bottlenecks, and collaborating with hardware architects, compiler engineers, and ML researchers to deliver production-grade tools.

A strong software engineering foundation and the ability to tackle a broad range of