英伟达Quality and Manufacturing Engineer
任职要求
• MS with 3+ years or equivalent experience in Electrical Engineering (EE), Computer Engineering (CE), Computer Science (CS), Systems Engineering, or a related field
• Rich experience at manufacturing and production test of chips, boards and systems.
• Background in creating new system tests or test conditions and good skills in Linux, Python, and Perl.
• Experience working with GPU/CPU system features and crafting test strategies.
• Deep understanding of product binning methods, optimization techniques, methods, trade-off analysis and tools for data analysis and statistics.
• Excellent problem solving, collaborative and interpersonal skills
Ways to stand out from the crowd:
• Background in rack-level test development
• Experience in Post-Silicon validation, SW&…工作职责
• Based on understanding a product feature, determine the best manufacturing stage for testing GPU/CPU hardware features. This could be ATE, socketed or board-level system test, rack-level test, or pod/cluster-level test, as needed. • Create new tests or test conditions based on an understanding of hardware features or learnings from customer returns or gaps in internal manufacturing stages. • Perform or automate test runs, analyze and visualize data to ensure a high-quality test, and guide debug for yield or escape issues. • Partner with test engineering and operations teams to implementing efficient manufacturable test solutions
According to audit and safety inspection requirements, conduct inspections across all stages of the operation chain, record any abnormalities, and ensure the authenticity and accuracy of audits and inspections. Be well-versed in audit and inspection standards, summarize and report exceptions as required. Coordinate promptly with relevant stakeholders in the chain to correct and rectify exceptions on-site, conduct regular reviews, and monitor improvements. Regularly inspect key fulfillment and safety items; promptly escalate and report to headquarters if major operational or safety risks are identified. Identify risk points in the fulfillment process through daily and special audits, and promote iterative improvements to process standards.
1. 可靠性方案规划：根据JEDEC规范和客户需求规划Flash新产品的可靠性验证方案，与设计和研发部门合作完成芯片可靠性指标评估，执行产品可靠性测试（包括WLR和component level，如Endurance、HTDR、LTDR、HTOL、ESD、latchup等）； 2. 测试计划制定：根据产品特性、客户要求及JEDEC标准，制定详细的Qualification可靠性测试计划、方案、技术规范与评判规则； 3. 失效分析与闭环：分析可靠性测试过程中的失效与问题，进行根本原因分析，提出改进建议，负责失效分析方案制订和报告编写，跟进解决方案的执行与有效性闭环验证； 4. 风险评估与报告输出：撰写、汇总并输出专业的产品Qualification可靠性测试报告、风险评估总结和改进建议； 5. DOE实验与改善：参与产品开发过程中与质量和可靠性相关问题的解决，计划并执行DOE实验验证，及时发现并安排失效分析，制定改善对策并跟进实施效果。
角色 Tesla服务工程团队正在寻找一位产品现场质量工程师，产品现场质量工程师能够结合现场失效情况以及运用后台数据分析，量化失效影响，并通过工程方法识别、分析失效和故障的根本原因，追踪问题并实施有效对策，最终提升产品的健康度、质量、可靠性、耐用性及客户体验。为了高效识别提升产品质量，产品现场质量工程师需要深入了解能源产品的运行特性，常见现场失效模式以及在设计，生产制造中可能对现场造成的质量影响。 工作内容 通过产品实时数据，后台工单数据监控产品现场表现，识别趋势性产品现场质量问题，并根据现场产品故障模式的严重性、发生频率以及影响成本确定问题调查以及解决的优先级。 运用第一性原理以及工程学提出故障失效假设，与失效分析团队协调合作，找到问题根本原因。 与设计工程，工厂质量以及服务团队合作，推动封堵和纠正措施的实施的落实并持续监控质量提升表现。 负责协调DFMEA分析过程，与跨部门团队（如设计、生产制造、服务团队等）合作，确保所有潜在的失效模式都被识别和评估，并最终推动现场问题的的解决。
1.Training System Development: Design and improve the team’s training framework and manuals based on business needs and team growth. Organize onboarding and ongoing training programs to continuously strengthen team expertise and service standards. 2.Quality Control Strategy & Implementation: Lead the establishment of quality standards and comprehensive quality assurance systems for the team (including sample checks, full checks, and process reviews). Conduct regular quality audits and assessments, drive issue rectification, and set up preventive and improvement measures targeting common errors. 3.Process Monitoring & Closed-Loop Management: Monitor key business processes such as merchant data upload, verification, and onboarding in real time. Use systematic indicators, sampling inspections, and automated tools to ensure rigorous quality monitoring. Analyze anomalies and issues with a data-driven approach, execute corrective actions, and follow up to guarantee the accuracy and integrity of team outputs. 4.Data Analysis & Continuous Optimization: Evaluate operational data as well as training and quality control feedback on a regular basis. Propose and implement improvements to enhance team efficiency and service quality. 5.Cross-Functional Collaboration: Work closely with Operations, Compliance, Product, and Sales teams to optimize processes and information flow, facilitating smooth merchant onboarding and ongoing success.