Job Overview
This role will chart a path into a new field at the intersection of Electronic Design Automation (EDA), Data Science and Machine Learning, applied to Semiconductor Design and Silicon Manufacturing flows.
The Pattern Analytics Senior Staff Engineer role requires an understanding of the state of the art in EDA, coupled with a creative approach to building products.
Technical skills required for this task will be able to imagine and then create new computational solutions, from prototype to full product implementation. Thus, the successful Pattern Analytics Senior Staff Engineer will work with a multi-disciplinary team to build and test completely new families of EDA products.
Responsibilities And Duties
- Develop software modules and shared libraries throughout a product life cycle, from prototype to customer release
- Work with a cross-functional teams across several disciplines to identify new approaches to layout analysis and define algorithmic solutions
- Implement testing and benchmarking automation for Pattern Analytics tools
- Assist in the creation of technical product documentation
- Troubleshoot customer issues after deployment and provide solid technical solutions
Qualifications
- Ph.D. or MS (with 3-5 years industry experience) in EE, CS or related engineering fields with strong computational and numerical analysis concentrations.
- Experience in Electronic Design Automation, and/or VLSI Physical Design Verification, and/or Mask Data Generation is a plus.
- Specific skills in semiconductor design and manufacturing:
- Physical design, place and route
- DRC checks, DFM checks, Pattern Matching checks, Printability checks
- Physical design ECOs, layout fixing and automation
- Practical Machine Learning and Data Science (including statistical analysis and modeling)
- Exploratory Data Analysis and Data Cleaning
- Feature Engineering
- Advanced ML (Deep-Learning Architectures, Transformers, etc.) is a plus
- Strong Database Development Skills are required. Specifically:
- Queries Development and Optimization SQL filtering, aggregation, sampling
- Graph representations, queries/traversal
- Multi-DB Query optimization, indices
- Server-based database implementation (such as PostgreSQL) and/or embedded database (such as SQLite)
- Programming Languages:
- Advanced Python 3, Javascript, SQL are required
- C++ and/or Java would be a strong plus
- Asynchronous programming
- Applications/Libraries for Data Visualization and Machine Learning
- Application/Libraries for Computational Geometry and VLSI Layout manipulation
