存储器件可靠性研发工程师

工作职责： 1. 制定并执行 NAND 可靠性表征与产品认证计划，确保符合 JEDEC 标准、内部要求及客户要求。 2.分析关键可靠性测试数据，包括耐久性、数据保持、读/编程干扰、跨温应力、HTOL 及其他 NAND 可靠性评估项目。 3.分析可靠性失效、异常数据和离群行为，识别潜在根因，并与跨职能团队协作推动改善措施。 4. 准备认证报告、风险评估、sign-off总结和技术结论，支持技术发布及客户认证决策。 5. 开发基于 AI/ML 的可靠性预测方法、筛选策略和数据自动化流程，提升测试覆盖率、工程效率和决策质量职位要求： 1. 微电子、电子工程、材料科学、物理、计算机科学、统计学或其他相关工程/理科专业硕士及以上学历。 2.扎实理解半导体器件、制造工艺、产品测试或可靠性工程基础知识。 3. 具备较强的分析思维、结构化问题解决能力、责任心，并愿意深入学习复杂的 NAND可靠性机制。 4. 具备良好的中英文沟通能力，能够清晰总结技术发现，并面向跨职能团队进行有效沟通。 5. 能够有效使用 AI工具提升工程效率、数据分析和流程自动化能力，同时具备 Python、C/C++、Perl、SQL、Excel、Power BI 或同等工具的基础编程能力。6. 优先条件：具备 NAND/NOR Flash、存储系统、可靠性测试、统计建模、机器学习或大规模数据分析相关经验或课程背景。 ESSENTIALDUTIES AND RESPONSIBILITIES: 1. Define and execute NAND reliabilitycharacterization and qualification plans in alignment with JEDEC, internal, andcustomer requirements. 2. Analyze key reliability test data, includingendurance, data retention, read/program disturb, cross-temperature stress,HTOL, and other NAND evaluations. 3. Analyze reliability failures, abnormaldata signatures, and outlier behaviors; identify potential root causes anddrive corrective actions with cross-functional teams. 4. Prepare qualificationreports, risk assessments, sign-off summaries, and technical conclusions tosupport technology release and customer qualification decisions. 5. DevelopAI/ML-based reliability prediction methods, screening approaches, and dataautomation flows to improve test coverage, engineering efficiency, anddecision-making quality. QUALIFICATIONS REQUIRED: 1. Master’s degree or abovein Microelectronics, Electrical Engineering, Materials Science, Physics,Computer Science, Statistics, or other relevant engineering/sciencedisciplines. 2. Solid understanding of semiconductor devices, fabricationprocesses, product testing, or reliability engineering fundamentals. 3. Stronganalytical thinking, structured problem-solving skills, ownership, andwillingness to learn complex NAND reliability mechanisms. 4. Good communicationskills in English and Chinese, with the ability to summarize technical findingsclearly for cross-functional teams. 5. Ability to effectively leverage AI toolsfor engineering productivity, data analysis, and workflow automation, togetherwith basic programming skills using Python, C/C++, Perl, SQL, Excel, Power BI,or equivalent tools. 6. Preferred Qualifications: Relevant experience orcoursework in NAND/NOR Flash, memory systems, reliability testing, statisticalmodeling, machine learning, or large-scale data analysis.