Company:
Qualcomm Semiconductor Limited
Job Area:
Engineering Group, Engineering Group > Hardware Engineering
General Summary:
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:
- Bachelor's degree in Computer Science, Electrical/Electronics Engineering, Engineering, or related field and 4+ years of Hardware Engineering or related work experience.
OR
Master's degree in Computer Science, Electrical/Electronics Engineering, Engineering, or related field and 3+ years of Hardware Engineering or related work experience.
OR
PhD in Computer Science, Electrical/Electronics Engineering, Engineering, or related field and 2+ years of Hardware Engineering or related work experience.
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:
- 8+ 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.
- Provide technical leadership and mentorship to junior engineers and cross-functional partners
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