Research Scientist, Generative AI Fashion (google)

google Multiple Location, United States 2024-10-28

Job posting number: #154693 (Ref:91389374213563078)

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Job Description

Qualifications

Minimum qualifications:

PhD degree in Computer Science, a related field, or equivalent practical experience.
One or more scientific publication submission(s) for conferences, journals, or public repositories.
Experience in computer vision and machine learning.
Experience coding in Python.

Preferred qualifications:

2 years of experience in coding.
1 year of experience owning and initiating research agendas.
Track record of publication in computer vision/graphics conferences (such as CVPR, ECCV, ICCV) or journals (such as SIGGRAPH, SIGGRAPH Asia, TPAMI).
View Orignal JOB on: italents.net
Expertise in image/video generation.
Expertise in diffusion.

Summary

PhD degree in Computer Science, a related field, or equivalent practical experience.
One or more scientific publication submission(s) for conferences, journals, or public repositories.
Experience in computer vision and machine learning.
Experience coding in Python.

Description

As an organization, Google maintains a portfolio of research projects driven by fundamental research, new product innovation, product contribution and infrastructure goals, while providing individuals and teams the freedom to emphasize specific types of work. As a Research Scientist, you'll setup large-scale tests and deploy promising ideas quickly and broadly, managing deadlines and deliverables while applying the latest theories to develop new and improved products, processes, or technologies. From creating experiments and prototyping implementations to designing new architectures, our research scientists work on real-world problems that span the breadth of computer science, such as machine (and deep) learning, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more.

As a Research Scientist, you'll also actively contribute to the wider research community by sharing and publishing your findings, with ideas inspired by internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world.

Come join the Apparel Machine Learning team. Our team built the successful virtual try-on feature on Google Search and Ads, and we're now expanding to work on video generation and virtual try-on for anyone. If you love generative AI, are excited about inventing and building models to generate images and videos, dig deeper into architectures, and invent new things, you've come to the right place. We have a lot of training data, compute, and passion to build the best virtual try on experience in the world. We're both publishing and launching a unique combination.

The US base salary range for this full-time position is $136,000-$200,000 + 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

Invent and build new generative AI-based models for fashion-focused generative AI experiences focused on images and videos.
Invent new architectures to enable the highest quality video generation.
Tune existing virtual try-on and garment generation.
Collaborate across Google Product Areas and Google DeepMind on novel generation techniques.
Author research papers to share and generate impact of research results across the team and in the research community.

Additional_instructions

Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Mountain View, CA, USA; New York, NY, USA; Seattle, WA, USA.