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Google Image Quality and Tuning Expert, Augmented Reality in Mountain View, California

Minimum qualifications:

  • Bachelor’s degree in Computer Science, Electrical Engineering, Computer Engineering, Physics, or a specialized field (e.g., Optics, Sensors, Audio/DSP, etc.), or equivalent practical experience.

  • 4 years of experience in developing hardware IP, ISP algorithms, image pipelines, consumer camera or computational photography techniques.

  • 4 years of experience programming in C++ or Python.

  • 4 years of experience working in a hardware technical environment, or 3 years of experience with an advanced degree.

  • Experience in camera and ISP tuning.

Preferred qualifications:

  • Master's degree or PhD in Electrical Engineering, Computer Engineering, Physics, or a related field (e.g., Optics, Sensors, Audio/DSP).

  • Familiarity with Matlab or similar signal data analysis tools.

  • Ability to program in C++ and Python.

Be part of a diverse team that pushes boundaries, developing custom silicon solutions that power the future of Google'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 be an expert in cameras, image quality, and image processing algorithms. You will have the unique opportunity to shape the imaging abilities in Augmented Reality (AR) products. You will be responsible for developing camera control strategies to optimize power, latency, and image quality of AR imaging functions.

The Google Augmented Reality team is a diverse group of experts tasked with building the foundations for great immersive computing and building helpful, delightful user experiences. We're focused on making immersive computing accessible to billions of people through mobile devices, and our scope continues to grow and evolve.

The US base salary range for this full-time position is $142,000-$211,000 + 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.

  • Lead characterization work for component image quality with a combination of lab and in field performance, across multiple applicant image processing flows. Structure characterization to uncover potential performance issues across the full range of scenes encountered by the product.

  • Recommend image quality improvements and work closely with tuning and image enhancement engineers to deliver imaging flows and tuning that meet quality, latency, and compute utilization requirements.

  • Communicate results and implications to a cross-functional team, and work cross-functionally to optimize hardware performance under established design constraints.

  • Develop characterization and reporting infrastructure to improve the team’s capability, efficiency, and uniformity.

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 https://careers.google.com/eeo/ and https://careers.google.com/jobs/dist/legal/OFCCPEEOPost.pdf If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form: https://goo.gl/forms/aBt6Pu71i1kzpLHe2.

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