דרושים » מדעים מדוייקים » Scientific Director, Physics

Required SoC Quality and Reliability Engineer, Cloud
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 state-of-the art SoCs that power these data centers by driving quality and reliability processes from the Integrated Circuit perspective. This is an opportunity to create silicon and follow it into the field (and back!) to drive improvements for the next-generations of chips.
In this role, you will understand Integrated circuit (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 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 robust silicon and package verification.
Execute comprehensive silicon and package qualification programs (including HTOL, ELFR, ESD/LU, b/HAST, etc.) and conduct in-depth failure analysis to resolve quality issues.
Extract and analyze large-scale 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, TDDB, NBTI) to predict device failure mechanisms and lifetime behaviors.

we are looking for a Algorithm and Applied AI Scientist (DSP).
As an Algorithm and Applied AI Scientist (DSP), you will serve as the technical lead for an innovative project focused on advanced signal processing and data analytics applications. You will work with unique datasets from various signal-generating sources, researching and developing novel models, and analysing, maturing, and extracting features that have a significant impact on industrial manufacturers globally. In this role, you will be instrumental in defining project objectives, identifying customer value, and pushing the team toward successful outcomes. Joining AI team offers ongoing professional growth in leadership, algorithm development, research, innovations, and technical data analysis.
A Day In Your Life:
Be the technical lead of an innovative project.
Develop a comprehensive understanding of industrial data by exploring its physical properties and the relationships among different data streams.
Oversee the full algorithm development cycle, spanning from initial problem definition to the deployment of production-ready feature-based AI models, SDLC starting from feature discovery that is being tracked by sensor behavior patterns.
Architect and build diverse predictive and anomaly classification models using sensor time-series and textual information.
You will gain a deep proficiency in the industrial world and the connection between datasets to generate actionable insights.
Utilize classic and cutting-edge technologies, such as Generative AI, transformers, TSFM, TGNN, deep learning, and traditional statistical methods, time-series, and textual data to generate actionable insights.
Partner with the product team and external customers to create data-driven solutions that address real-world business needs.

We are seeking an experienced and self-driven Systems Engineering Functional Manager to lead our systems engineering team for our CT/AMI detection platform (DMS). This team is responsible for the full lifecycle of system-level development from systems design, requirements management, architecture design, execution of technical reviews, setting the integration plan to verification, validation, and regulatory compliance.

Your role:
Lead and mentor a multidisciplinary systems engineering team, fostering growth, collaboration, and technical excellence.
Provide strategic and hands-on technical guidance in the development of CT/AMI detection platforms.
Oversee engineering planning and execution to support complex project ensuring timelines and quality standards are met.
Resource assignment and prioritization including headcount and budget management.
Working across functions and team boundaries to define, design, and implement the next generation of products.
Decision making in cross-disciplinary and architectural aspects.
Drive continuous improvement in engineering and systems engineering processes and tools.
Support audits and regulatory inspections as a subject matter expert.
Represent DMS System Design in global engineering forums and initiatives.