Machine Learning, Architect
Location
Sunnyvale, CA | United States
Job description
Job Description and Requirements
We are looking for an experienced architect in Machine Learning, Generative AI and Data Analytics as applied to the domain of Design Automation for semiconductor manufacturing. You will play a critical role in defining strategic directions and you will be responsible for architecting the solution that takes us from concepts to products. In this role you will work closely with other leaders and architects of the product portfolio, and you will drive the thoughtful and systematic application of ML and AI technology to solve problems in the semiconductor manufacturing domain.
Expected Qualifications:
- Advanced degree (PhD or MSc) in Electrical Engineering, Computer Science, Applied Mathematics, Mechanical Engineering or Data Science
- 10+ years of experience in the domain of semiconductor engineering, processing, design for manufacturing, DTCO, design implementation or adjacent areas
- Strong computer skills applied continuously and without interruptions using one or more of the relevant to our group languages (C/C++, python, Matlab, perl, tcl/tk)
- Demonstrable expertise in Machine Leaning and AI by previous large projects in such domains
- Strong analytical and problem solving abilities and ability to communicate ideas and formulate and solve problems that matter to our customers
The base salary range across the U.S. for this role is between $210,000-$314,000. In addition, this role may be eligible for an annual bonus, equity, and other discretionary bonuses. Synopsys offers comprehensive health, wellness, and financial benefits as part of a of a competitive total rewards package. The actual compensation offered will be based on a number of job-related factors, including location, skills, experience, and education. Your recruiter can share more specific details on the total rewards package upon request.
Inclusion and Diversity are important to us. Synopsys considers all applicants for employment without regard to race, color, religion, national origin, gender, sexual orientation, gender identity, age, military veteran status, or disability.
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