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abra R&D is seeking an Embedded Python Developer to join our team! We are looking for a Python Software Engineer to develop the application layer of a multidisciplinary autonomous drone system. You will work on the drone’s main onboard computer, building high?level logic, integrating algorithms, and creating communication and control flows across multiple subsystems. Responsibilities
* Develop application?level and high?level control logic for an autonomous platform.
* Implement management modules and integrate external algorithms (SO/DLL).
* Work with communication protocols (UDP, REST, DBS, CTP).
* Collaborate with multidisciplinary teams (systems, electronics, algorithms).
* Participate in integration and field testing when needed.

Be part of a team that pushes boundaries, developing custom silicon solutions that power the future of our company's direct-to-consumer products. You'll contribute to the innovation behind products loved by millions worldwide. Your expertise will shape the next generation of hardware experiences, delivering unparalleled performance, efficiency, and integration.
As a Foundry, IP and Package Technologist, you will directly collaborate with architecture teams, external manufacturing partners (foundries and packaging vendors) to coordinate the technical stabilization and yield ramp of our custom silicon. You will be responsible for in-depth yield analysis, debugging process-design interactions, and driving corrective actions to resolve manufacturing defects. Your expertise in root-cause analysis and process optimization will ensures that our groundbreaking chips ramp up seamlessly from initial silicon arrival to high-volume production, directly enabling the future of our computing capacity.
The AI and Infrastructure team is redefining whats possible. We empower our company customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers, our company Cloud customers, and billions of our company users worldwide.
We're the driving force behind our company's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for our company Cloud, our company Global Networking, Data Center operations, systems research, and much more.
Responsibilities
Drive yield modeling for NPIs, support pre silicon activities in Foundry aspects of new devices.
Lead process debug investigations, utilizing inline data to isolate the root cause of yield limiters, distinguishing between random defects and systematic marginalities.
Drive yield improvements by executing advanced statistical analysis on high-volume manufacturing data, identifying subtle process-design interactions that impact performance, and defining the necessary corrective actions.
Collaborate with cross-functional design, product, and test teams to triage silicon failures, distinguishing between design bugs, foundry process marginalities, and packaging interaction issues to support New Product Introduction (NPI).
Partner with architecture and design teams to feed back critical manufacturing constraints into future product definitions, ensuring that next-generation chiplets are architected to be resilient to known process variances.

Be part of a team that pushes boundaries, developing custom silicon solutions that power the future of our company's direct-to-consumer products. You'll contribute to the innovation behind products loved by millions worldwide. Your expertise will shape the next generation of hardware experiences, delivering unparalleled performance, efficiency, and integration.
In this role, you will help build SoCs by driving quality and reliability processes from the Integrated Circuit (IC) perspective. Working with various cross-functional teams, you will develop quality and reliability specifications, develop and deploy design guidelines, and develop and execute test plans. Within the larger organization, you will collaborate with global hardware quality and reliability, silicon design, validation, and engineering teams. You will have an understanding of IC flows, wafer processing, testing, qualification, yield, reliability, and failure analysis.
The ML, Systems, and Cloud AI (MSCA) organization at our company designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all our company services (Search, YouTube, etc.) and our company Cloud. Our end users, Cloud customers and the billions of people who use our company services around the world.
We prioritize security, efficiency, and reliability across everything we do - from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including our company Clouds Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.
Responsibilities
Define and lead qualification hardware and test developments in front of internal teams and external vendors.
Define and execute Silicon and package qualification activities (e.g., HTOL, ELFR, ESD/LU, b/HAST, THB, etc.).
Extract, manipulate, and analyze large volumes of data from Silicon and package qualification programs (e.g., HTOL, ELFR, ESD, LU, UHAST, TCT, etc.), High Volume MFG, and field returns to identify failure mechanisms, reliability trends, and opportunities for yield, quality, and reliability improvement.
Own cross-functional investigation of IC quality and reliability issues to identify root causes and develop solutions (e.g., RMA Triage, Analytics, Failure Analysis, etc.).
Develop and implement physics-based statistical Quality and Reliability models (e.g., ELF, TDDB, NBTI, HCI, Time zero failures, etc.) to predict silicon device failure mechanisms, degradation patterns, and lifetime behaviors.