Job Overview
This is a Senior Architect position in the Mask Solutions team. In this role you are expected to lead the development of new areas within the Mask Solutions product portfolio. The areas of responsibility will include the infrastructure system and the data management system across multiple tools, and solutions related to overall system optimization and data flow optimization. Additionally, you are expected to work on, or directly influence the architecture and design of full-chip mask solutions software for large-scale pattern cataloguing and analytics. In this work, you are also expected to set the path on key areas, such as judicious use of ML/AI in the domain of mask optimizations and use of HPC/GPU in image processing for deployment of Synopsys tools in OEM solutions. From this position you will be able to influence technical directions and be part of the team that is commissioned to solve higher-level problems of systemic complexity, by leveraging multiple Synopsys assets and adjacent components.
Responsibilities And Duties
- Propose alternative architectures that can leverage new HPC and GPU platforms in optimal ways as applied in the mask solutions domain.
- Develop high-capacity solutions in the area of pattern cataloguing and pattern analytics. Develop robust ways to compute and store suitable annotations that capture the physical behavior of these pattern libraries.
- Work closely together with other architects and senior architects in the team to reach optimal solutions to a diverse set of problems in the general infrastructure space, that generally involve optimal problem partitioning and scalable job distribution to take advantage of large compute resources (100K+ cpu cores).
- Integrate the right dose of ML/AI concepts to affect quality (QOR) or runtime (TAT) of core technologies in the mask solutions domain.
Qualifications
- MS/Ph.D. in CS/CE/EE or other computation-oriented engineering majors
- Substantial experience (15+ years) in EDA or software development in a scientific or technical domain.
- Deep experience in end-to-end software development with agile concepts: iteration of requirements, unit tests, development, testing, optimization, documentation
- Significant and demonstrable experience in optimization, computational geometry, scientific computing, system level optimization, software architecture of systems with high complexity, parallel computing.
- Deep knowledge in a large subset of relevant technical skills, such as in OOP (C, C++), interpreter languages (python, tcl/tk, perl), ML/AI (use of pytorch, tensorflow), GPU programming, image processing packages, matlab, linux.
