The business problem is to enhance the efficiency and effectiveness of semiconductor validation processes at the company by designing, developing, and deploying AI-driven solutions.
Requirements
- Hands-on experience with Python and AI/ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn)
- Familiarity with data analysis and engineering concepts
- Strong problem-solving and analytical skills
- Currently pursuing a University degree in Computer Science, Electrical Engineering, Computer Engineering, or a related field.
- Demonstrated initiative and ownership of technical projects
Responsibilities
- Own and deliver end-to-end AI projects, from ideation to deployment, aimed at automating and improving post-silicon validation workflows.
- Collect, preprocess, and analyze validation data to identify patterns, anomalies, and opportunities for AI-driven automation and decision-making.
- Design, train, and evaluate machine learning models to solve complex validation challenges, such as anomaly detection, predictive maintenance, and test optimization.
- Integrate AI models and solutions into existing post-silicon validation software and hardware environments, ensuring scalability and robustness.
- Develop and maintain scripts and tools to automate data collection, model training, and deployment processes.
- Investigate and resolve issues related to AI model performance, integration, and data inconsistencies in validation workflows.
- Create comprehensive documentation for AI solutions, workflows, and results, facilitating future adoption and team learning.
Other
- Currently pursuing a University degree in Computer Science, Electrical Engineering, Computer Engineering, or a related field.
- Excellent communication and collaboration abilities
- Student / Intern (Fixed Term) job type
- Shift 1 (United States of America)
- Primary Location: San Jose, California, United States
