MBIST Diagnostics Engineer - Sr Staff/Staff Engineer
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. 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. 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 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
