Staff Engineer (Machine Learning)
SynopsysRole Summary
The Staff Engineer (Machine Learning) role involves designing and developing machine learning-based optimization applications for advanced chip design. The position is part of the Machine Learning Center of Excellence in Synopsys’ Silicon Design & Verification business.
Experience Level
Mid-level; requires 5+ years of experience in chip design or related fields.
Responsibilities
Key responsibilities include:
- Designing and developing machine learning-based optimization applications for chip design.
- Integrating ML-driven solutions into EDA tools.
- Automating chip design flows using scripting languages.
- Collaborating with teams to enhance design performance and efficiency.
- Conducting research and prototyping new design methodologies.
- Staying current with trends in silicon design and machine learning.
Requirements
Required skills and experience:
- Bachelor’s, Master’s, or PhD in Electrical Engineering, Computer Science, or related field.
- 5+ years of experience in chip design or related domains.
- Strong programming and automation skills in Perl, Python, Tcl, or shell scripting.
- Solid understanding of Unix/Linux environments.
- Knowledge of RTL design, synthesis, and EDA processes.
- Familiarity with machine learning principles and low power design techniques.
Education Requirements
Bachelor’s, Master’s, or PhD in Electrical Engineering, Computer Science, Computer Engineering, or a related discipline.
About the Company
Company: Synopsys
Headquarters: Mountain View, California, USA
Synopsys is a leading company in electronic design automation (EDA) and semiconductor IP solutions. It provides tools and services for designing and verifying complex semiconductor devices and systems. The company plays a pivotal role in the semiconductor industry, helping engineers innovate and deliver higher-quality products faster. Synopsys is committed to advancing technology standards and offers a range of software and hardware solutions to its clients globally.
