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we are seeking a Systems Applications Engineer to serve as a key technical resource for equipment readiness, system bring-up, and ongoing product support. In this role, you will partner closely with NPI Program Management, Engineering, suppliers, and cross-functional teams to support bills of material, evaluate design and assembly changes, ensure system and subsystem test coverage, and drive resolution of equipment issues. You will become a technical expert in prober operation and bring-up, helping ensure timely response, effective troubleshooting, and field validation of corrective actions.



Partner with NPI Program Management to understand, manage, and assess bills of material for current and future equipment configurations.
Evaluate BOM changes, design documentation, assembly requirements, and related technical updates to support product readiness and manufacturability.
Review system and subsystem test coverage to help ensure required tests exist, are properly executed, and support product quality expectations.
Work closely with Teradyne Engineering and external suppliers to troubleshoot current tool failures, identify root cause, and drive corrective action.
Support implementation of corrective actions and ensure appropriate field validation is completed.
Develop deep technical expertise in prober operation, system bring-up, and equipment behavior.
Serve as a first line of technical response for prober issues, ensuring timely escalation, clear communication, and effective remedies.
Collaborate across engineering, operations, suppliers, and field teams to improve equipment performance, reliability, and supportability.

Required SOC Quality and Reliability Engineer, Cloud
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Tel Aviv, Israel; Haifa, Israel.
About the job
In this role, youll work to shape the future of AI/ML hardware acceleration. You will have an opportunity to drive cutting-edge TPU (Tensor Processing Unit) technology that powers our most demanding AI/ML applications. Youll be part of a team that pushes boundaries, developing custom silicon solutions that power the future of our TPU. You'll contribute to the innovation behind products loved by millions worldwide, and leverage your design and verification expertise to verify complex digital designs, with a specific focus on TPU architecture and its integration within AI/ML-driven systems.
Our data centers are the most advanced in the world. In this role, you will help build the SoCs that power these data centers by driving quality and reliability processes from the integrated circuit perspective. You will create silicon and follow it into the field (and back) to drive improvements for the next generations of chips.
You will have an understanding of IC flows, wafer processing, testing, qualification, yield, reliability, and failure analysis. You will work with various cross functional teams to develop quality and reliability specifications, develop and deploy design guidelines, and develop and execute and test plans. Within the larger organization you will collaborate with global hardware quality and reliability teams, silicon design, validation and engineering teams.The AI and Infrastructure team is redefining whats possible. We empower our customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity.
Responsibilities
Drive the strategic definition and development of design-for-reliability (DfR) guidelines, collaborating with cross-functional subject matter experts to integrate reliability into early design stages.
Define and lead the development of qualification hardware and test methodologies, managing internal teams and external vendors to ensure silicon and package verification.
Execute comprehensive silicon and package qualification programs (including high-temperature operating life (HTOL), early life failure rate (ELFR), electrostatic discharge/latch-up (ESD/LU), biased highly accelerated stress test (b/HAST), etc.) and conduct failure analysis to resolve quality issues.
Extract and analyze data from qualification programs, high-volume manufacturing, and field returns to identify failure mechanisms and trends for yield and reliability optimization.
Develop and implement physics-based statistical Quality and Reliability models (e.g., ELF, time-dependent dielectric breakdown (TDDB), negative bias temperature instability (NBTI) to predict device failure mechanisms and lifetime behaviors.

* Full end-to-end responsibility for the global Demand Planning process
* Build, analyze, and continuously improve demand forecasts based on historical data, market trends, and sales projections
* Lead the monthly S&OP process with global stakeholders (Sales, Marketing, Finance, Operations)
* Work closely with regional sales teams to collect, challenge, and validate forecasts
* Perform statistical analyses to identify trends, seasonality, and demand anomalies
* Monitor and manage forecast KPIs (Forecast Accuracy, Bias) and drive continuous improvement
* Translate demand forecasts into supply plans in collaboration with Supply Planning
* Identify risks and opportunities in demand and escalate them to management in real time
* Work with ERP systems (e.g., NetSuite) and planning tools (advanced Excel / BI tools)
* Lead process improvement initiatives and implement Demand Planning best practices
* Build management reports and decision-support dashboards
* Align financial forecasts (Budget / Forecast) with operational forecasts

Subsidiary:
Alma LTD

Required SOC Quality and Reliability Engineer, Cloud
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Tel Aviv, Israel; Haifa, Israel.
About the job
In this role, youll work to shape the future of AI/ML hardware acceleration. You will have an opportunity to drive TPU (Tensor Processing Unit) technology that powers our most demanding AI/ML applications. Youll be part of a team that pushes boundaries, developing custom silicon solutions that power the future of our TPU. You'll contribute to the innovation behind products loved by millions worldwide, and leverage your design and verification expertise to verify complex digital designs, with a specific focus on TPU architecture and its integration within AI/ML-driven systems.
Our data centers are the most advanced in the world. In this role, you will help build the state-of-the-art SoCs that power these data centers by driving quality and reliability processes from the Integrated Circuit perspective. You will have an opportunity to create silicon and follow it into the field and back to drive improvements for the next-generations of chips.
You will have an understanding of Integrated Circuit (IC) flows, wafer processing, testing, qualification, yield, reliability, and failure analysis is expected. You will work with various cross-functional teams to develop quality and reliability specifications, develop and deploy design guidelines, and develop and execute and test plans. You will collaborate with global hardware quality and reliability teams, silicon design, validation and engineering teams.The AI and Infrastructure team is redefining whats possible.
Responsibilities
Lead the strategic definition and development of Design-for-Reliability (DfR) guidelines, collaborating with cross-functional subject matter experts to integrate reliability into early design stages.
Establish and direct the development of qualification hardware and test methodologies, managing internal teams and external vendors to ensure silicon and package verification.
Execute comprehensive silicon and package qualification programs (including high-temperature operating life (HTOL), early life failure rate (ELFR), electrostatic discharge and latch-up (ESD/LU), and biased highly accelerated stress test (b/HAST)) and conduct in-depth failure analysis to resolve quality issues.
Analyze data from qualification programs, high-volume manufacturing, and field returns to identify failure mechanisms and trends for yield and reliability optimization.
Develop and implement physics-based statistical quality and reliability models (e.g., early life failure (ELF), time-dependent dielectric breakdown (TDDB), or negative bias temperature instability (NBTI)) to predict device failure mechanisms and lifetime behaviors.