Silicon Technology and Architecture Engineer, Augmented Reality - Google
Mountain View, CA
About the Job
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Mountain View, CA, USA; San Diego, CA, USA.Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.
Minimum qualifications:
- Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field, or equivalent practical experience.
- 8 years of experience from specifying and implementing features on mobile or AR/VR device platforms through to successful integration or product launch.
Preferred qualifications:
- Experience with mobile or XR software, silicon architecture development, or product architecture definition.
- Experience demonstrating a track record in system-on-chip silicon architecture or hardware/systems design and performance/power tradeoffs for consumer products.
- Experience in systems engineering technical leadership and bringing hardware, software, sensing, and computer vision algorithm solutions together through cross-functional team collaboration
- Experience and knowledge spanning system engineering, software, perception architecture, imaging, sensing, or silicon architecture.
- Ability to present complex technical topics to a multi-level and multi-disciplinary of key work partners both internally and externally to Engineering.
About the job
Our computational challenges are so big, complex and unique we can't just purchase off-the-shelf hardware, we've got to make it ourselves. Your team designs and builds the hardware, software and networking technologies that power all of Google's services. As a Hardware Engineer, you design and build the systems that are the heart of the world's largest and most powerful computing infrastructure. You develop from the lowest levels of circuit design to large system design and see those systems all the way through to high volume manufacturing. Your work has the potential to shape the machinery that goes into our cutting-edge data centers affecting millions of Google users.
The US base salary range for this full-time position is $221,000-$314,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.
Responsibilities
- Drive and create internal processes to ensure high quality Silicon definition, planning and timely execution, while owning internal silicon roadmap to support Google AR Engineering
- Propose and negotiate silicon requirements with internal cross-functional teams and external vendors that include platform software, perception architecture and algorithms, HW engineering, Product Management, Supply Chain, and silicon vendors
- Work with hardware and optical engineers to analyze component selection trade-offs
- Help focus design teams on meeting schedules and unblocking technical issues by organizing the right resources to resolve issues with data-driven decisions
- Perform end-to-end data flows, duty cycle and memory hierarchy analysis, memory management benchmarking, and/or latency simulations to inform solutions to achieve product intent and critical use cases.
Source : Google