Machine Learning Software Engineer, Synopsys

Responsibilities:

• Designing and supporting machine learning applications for cutting-edge ICs and SoCs within the Machine Learning Center of Excellence (ML CoE) team.
• Identifying opportunities in VLSI design workflows and proposing solutions using generative AI and machine learning techniques to improve VLSI design quality and designer productivity.
• Designing and implementing highly efficient data structures and algorithms.
• Committing to deliver top-quality production software that exceeds customer expectations.
• Collaborating with cross-functional teams to innovate and develop new features for AI-driven EDA applications.

Requirements & Skills:

• Driving innovation in AI-driven EDA applications to help customers design complex chips.
• Contributing to the development of the industry’s first AI-driven implementation platform, DSO.ai.
• Prototyping, designing, and developing new features for AI-driven EDA tools.
• Enhancing the performance and quality of Synopsys’s AI-driven EDA tools.
• Collaborating with global teams to push the boundaries of AI and EDA integration.
• Strong CS fundamentals (data structures, algorithms, object-oriented design, computer architecture, operating systems, distributed systems).
• Experience with developing machine learning projects/applications.
• Familiarity with VLSI digital design and implementation flows like synthesis, place, and route.
• BSc/MSc or PhD degree in Electrical Engineering, Computer Science, or related discipline.
• 3-5 years of experience in a similar role.
• Working knowledge in developing and maintaining complex Python/C/C++ applications in a Unix/Linux environment.
• Knowledge of machine learning, design of algorithms with efficient data structures, neural networks, and pattern matching.
• Knowledge of EDA design tool implementation and signoff flows.