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Research Engineer, Generative Media at Google · Trevo
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Job Description
What you'll do
Design, implement, train, and evaluate deep learning architectures—particularly diffusion models and transformers—for image and video synthesis.
Develop and apply algorithms in computer vision, graphics, and machine learning for Google applications, focusing on computational photography, computational videography, and content creation.
Conduct both fundamental and applied research to identify and solve creative, novel problems that revolutionize editing, and creation of visual media.
Leverage deep theoretical and practical knowledge to prototype new technologies that unlock visual experiences for users.
Build upon our strong track record of publishing graphics venues (with previous publications including Dreambooth, GameNGen, ObjectMate, LightLab, and many more), and successfully transfer these innovations into Google products that reach millions to billions of users.
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 .
Bachelor’s degree or equivalent practical experience.
5 years of experience leading a research agenda.
Experience in designing, training, and evaluating deep generative models (e.g., Diffusion Models, Transformers, GANs) for media synthesis and manipulation (image, video, audio).
Experience with experimentation, dataset curation, eval systems, and building ML pipelines.
Experience with machine learning, computer vision, and deep learning.
One of more scientific publication submission(s) for conferences, journals, or public repositories (such as CVPR, ICCV, NeurIPS, ICML, ICLR, etc.).
Nice to have
Master's degree or PhD in Computer Science, or a related technical field.
3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
2 years of experience with Machine Learning and Deep Learning frameworks (e.g., TensorFlow, PyTorch).
Experience or deep domain familiarity with Machine Learning, Computer Vision, Generative AI, or 3D graphics/rendering technologies.
About the jobAt Google, research-focused Software Engineers are embedded throughout the company, allowing them to setup large-scale tests and deploy promising ideas quickly and broadly. Ideas may come from internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world.
From creating experiments and prototyping implementations to designing new architectures, engineers work on real-world problems including artificial intelligence, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more. But you stay connected to your research roots as an active contributor to the wider research community by partnering with universities and publishing papers.
The Creative Camera team mission is to imagine and build the future of photography and videography. Our team is reinventing digital imagery: from pioneering new generative and diffusion models for creating the highest-quality images and videos possible, to creating entirely new ways of capturing and reliving our experiences.
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.