Diagnostics/AI Engineer - Sr. Staff or Staff Engineer

General Summary:

As a leading technology innovator, Qualcomm pushes the boundaries of what''s possible to enable next-generation experiences and drives digital transformation to help create a smarter, connected future for all. As a Qualcomm Hardware Engineer, you will plan, design, optimize, verify, and test electronic systems, bring-up yield, circuits, mechanical systems, Digital/Analog/RF/optical systems, equipment and packaging, test systems, FPGA, and/or DSP systems that launch cutting-edge, world class products. Qualcomm Hardware Engineers collaborate with cross-functional teams to develop solutions and meet performance requirements.

Minimum Qualifications:

Bachelor''s degree in Computer Science, Electrical/Electronics Engineering, Engineering, or related field and 4+ years of Hardware Engineering or related work experience. ORMaster''s degree in Computer Science, Electrical/Electronics Engineering, Engineering, or related field and 3+ years of Hardware Engineering or related work experience. ORPhD in Computer Science, Electrical/Electronics Engineering, Engineering, or related field and 2+ years of Hardware Engineering or related work experience.

General Summary:

We are seeking an experienced and innovative professional to lead the development of advanced memory diagnostic methodologies and tools for next-generation SoCs. This role involves driving cutting-edge solutions in DRAM testing, failure analysis, and AI/ML-based pattern recognition to improve memory yield and reliability across high-volume manufacturing environments.

Minimum Qualifications:

• Experience in developing diagnostic tools for emerging memory technologies.
• Exposure to data analytics platforms for large-scale failure analysis.
• Bachelor??s or Master??s degree in Electrical engineering, Computer Engineering, or related field.

Preferred Qualifications:

• 12+ years of experience in memory diagnostics, DRAM test, and failure analysis in advanced SoC environments.
• Deep understanding of fault isolation, redundancy schemes, fault models and memory test algorithms.
• Experience with AI/ML techniques applied to pattern recognition or data analytics in semiconductor test or yield domains.
• Proficiency in Python, Perl, TCL and data visualization tools.
• Experience with HTOL, RMA debug, and high-volume manufacturing diagnostics.
• Knowledge of memory redundancy, error correction, and self-repair mechanisms.
• Knowledge of implementation of MBIST solutions using industry-standard tools (e.g., Mentor Tessent, Synopsys etc).
• Strong analytical and problem-solving skills with a data-driven mindset.
• Excellent communication and collaboration skills in a cross-functional, global environment

Key Responsibilities:

• Develop and enhance memory diagnostic methodologies including DRAM-specific diagnostics.
• Define and develop memory test and repair algorithms (BIRA, ECC, redundancy analysis)
• Isolate failing memory locations and analyze failure signatures to support yield improvement, RMA, and HTOL debug.
• Evaluate and improve memory yield through data analysis and test coverage enhancements.
• Design and implement AI/ML-based pattern recognition tools to enable advanced bitmapping and failure characterization beyond the capabilities of current tools.
• Collaborate with silicon validation, product engineering, and yield analysis teams to correlate diagnostics with silicon behavior.
• Drive innovation in diagnostic algorithms and tool development to support future technology nodes and memory architectures.