ML Software Engineer Intern - AI/CAD Integration

Responsibilities

• Design and implement code for training/serving ML models in chip design workflows
• Automate creation of large datasets for training models
• Integrate ML models into existing chip design software infrastructure
• Write comprehensive tests and documentation
• Collaborate with engineers to understand model requirements and deployment needs
• Participate in code reviews and follow software engineering best practices
• Research and evaluate new technologies for ML model serving and deployment

Requirements

• Currently pursuing a degree in Computer Science, Electrical Engineering, or related field
• Availability to work at least part-time starting in Fall 2026
• Strong Python programming skills with experience in scripting and automation
• Understanding of software engineering principles and code organization
• Experience with data processing libraries (pandas, numpy, scipy)
• Familiarity with machine learning frameworks (PyTorch, TensorFlow, scikit-learn)
• Basic understanding of file I/O, data parsing, and format conversion
• Experience with version control systems (Git) and collaborative development

Preferred Skills

• Exposure to CAD tools or EDA software (Cadence, Synopsys, Mentor Graphics, etc.)
• Knowledge of chip design file formats (GDSII, LEF/DEF, Verilog, SPICE)
• Experience with shell scripting (bash) and command-line tools
• Understanding of semiconductor design concepts
• Familiarity with Linux environments
• Experience with workflow automation and batch processing systems
• Knowledge of data visualization tools (matplotlib, plotly) for design analysis
• Understanding of software testing frameworks and debugging techniques