AI/ML Engineer_Diagnostics & Yield_ Up to Senior Staff

Qualcomm is 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, focusing on extracting actionable insights from complex data to enhance product quality and manufacturing efficiency.

Must Have

• 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/PhD with less experience)
• Design and implement AI/ML models to analyze silicon yield data
• Develop predictive models to forecast yield trends
• Apply deep learning and statistical techniques to improve scan diagnostic resolution and fault localization
• Collaborate with test engineering teams to collect, clean, and structure large-scale test and yield datasets
• Integrate data from ATE, DFT, and fab & assembly process logs for comprehensive analysis
• Build scalable pipelines and tools that integrate AI models into existing diagnostic and yield analysis workflows
• Partner with design, test, and manufacturing teams to understand challenges and translate them into AI solutions

Good to Have

• 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

Perks & Benefits

• World-class health benefit option providing world-class coverage to employees and their eligible dependents
• Programs designed to help employees build and prepare for a financially secure future
• Self and family resources to build emotional/mental strength and resilience, as well as define purpose
• Wellbeing programs and resources offering support to help employees Live+Well and Work+Well

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.