Company:
Qualcomm Semiconductor Limited
Job Area:
Engineering Group, Engineering Group > ASICS Engineering
General Summary:
As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next-generation experiences and drives communication and data processing transformation to help create a smarter, connected future for all. We are seeking a highly motivated and technically skilled AI Applications Engineer to lead the development and deployment of artificial intelligence solutions aimed at improving silicon & assembly yield analysis and advanced diagnostics in semiconductor manufacturing. This role bridges the gap between advanced machine learning techniques and semiconductor test engineering, with a focus on extracting actionable insights from complex data to enhance product quality and manufacturing efficiency.
Minimum Qualifications:
• Bachelor's degree in Science, Engineering, or related field and 6+ years of ASIC design, verification, validation, integration, or related work experience.
OR
Master's degree in Science, Engineering, or related field and 5+ years of ASIC design, verification, validation, integration, or related work experience.
OR
PhD in Science, Engineering, or related field and 4+ years of ASIC design, verification, validation, integration, or related work experience.
Key Responsibilities:
- AI Strategy & Development
- Design and implement AI/ML models to analyze silicon yield data and identify patterns, anomalies, and root causes of failures.
- Develop predictive models to forecast yield trends and proactively address potential issues.
- Apply deep learning and statistical techniques to improve scan diagnostic resolution and fault localization.
- Data Engineering & Analysis
- Collaborate with test engineering teams to collect, clean, and structure large-scale test and yield datasets.
- Integrate data from ATE (Automated Test Equipment), DFT (Design for Test), and fab & assembly process logs for comprehensive analysis.
- Tool & Workflow Integration
- Build scalable pipelines and tools that integrate AI models into existing diagnostic and yield analysis workflows.
- Work closely with EDA vendors and internal software teams to enhance tool capabilities with AI-driven features.
- Cross-Functional Collaboration
- Partner with design, test, and manufacturing teams to understand challenges and translate them into AI solutions.
- Communicate findings and recommendations to stakeholders through clear visualizations and reports.
Preferred Qualifications:
- Master’s or Ph.D. in Electrical Engineering, Computer Science, Data Science, or related field.
- Strong coding skills in Python and experience building AI-driven applications.
- Hands-on experience with GenAI concepts (LLMs, RAG, prompt engineering) and frameworks like LangChain.
- Solid foundation in data analytics and ability to learn semiconductor workflows quickly.
- Excellent communication skills in English; proven ability to lead technical initiatives.
- Strong understanding of semiconductor test methodologies, scan diagnostics, and yield analysis.
- Familiarity with DFT concepts, fault models, and EDA tools (e.g., Synopsys, Cadence).
- Experience with AI applications in semiconductor manufacturing or test engineering.
- Background in deploying AI models in production environments.
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