Senior Software Engineer, Computational Photography and Generative AI

Senior • On-site

$166,000 - $244,000/yr

Mountain View, CA , +1

Minimum qualifications:

Bachelor’s degree or equivalent practical experience.
5 years of experience with software development in one or more programming languages.
3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
3 years of experience with computer vision and image processing.
3 years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).

Preferred qualifications:

Master's degree or PhD in Computer Science or related technical field.
5 years of experience with data structures/algorithms.
Experience in machine learning or neural networks.
Experience with Natural Language Processing.
Strong programming skills in C/C++, Python.

About the job

Our team aims to invent and develop amazing innovative experiences for the users of Pixel phones and Google Photos. We use computational photography and machine learning to produce new kinds of pictures, videos, and photographic experiences. Our goal is to make pictures/videos with very high quality that are also engaging, fun, or magical - images that astonish people.

Our technologies typically combine "classical" vision and graphics with deep learning. We then optimize our algorithms to run fast on mobile devices or efficiently on servers, where hardware capabilities are limited. We work with several product teams, including the Google Camera App team and Google Photos, and collaborate extensively with other research teams. We focus on technologies that can be launched within 1-2 years and shift to be implemented on hardware for even longer term impact across Google.

The Platforms and Devices team encompasses Google's various computing software platforms across environments (desktop, mobile, applications), as well as our first party devices and services that combine the best of Google AI, software, and hardware. Teams across this area research, design, and develop new technologies to make our user's interaction with computing faster and more seamless, building innovative experiences for our users around the world.

The US base salary range for this full-time position is $166,000-$244,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. 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

Write and test product or system development code.
Design and implement solutions in one or more specialized ML areas, leverage ML infrastructure, and demonstrate expertise in a chosen field.
Invent and develop innovative AI features for images and photography, creating magical and innovative user experiences.
Conduct end-to-end work from research to product development within the images, camera, and video domains, and applying innovative research in vision/graphics/ML.
Develop cutting-edge technologies to revolutionize the representation, editing, and creation of visual media, with a focus on computational photography and videography.

Google

Google LLC started as a PhD project by Larry Page and Sergey Brin in 1998 at Stanford University. Google LLC has blossomed into a behemoth of the tech world. With its mission to organize the world's information and make it universally accessible and useful, Google’s search engine is its crown jewel. Online advertising, via AdWords and AdSense, forms the backbone of its financial success. Beyond search, Google has ventured into cloud computing, hardware, and software development. The innovative PageRank algorithm revolutionized search engine technology, and surviving the dot-com bubble burst and going public in 2004 spurred its meteoric growth. Acquiring YouTube stands as a testament to Google’s strategic expansion.