Research Engineer, Generative Media, DeepMind
Our team's mission is to build frontier generative media experiences. We are pushing the boundaries of what is possible by developing real-time, interactive video models like Genie, as well as exciting new applications and capabilities.
We have a proven track record of researching and delivering foundational generative models for video and action-controllable virtual worlds, as well as applications such as video stylization, reference-to-video generation, and precise object insertion and removal.
Artificial intelligence will be one of humanity’s most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority.
We are pushing the boundaries across multiple domains. Our global teams offer diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.
- Design, implement, train, and evaluate novel deep learning models for real-time generative media, including video-audio synthesis, manipulation, and understanding.
- Develop and optimize algorithms and systems for AI experiences on Omni platforms, focusing on live dialog, live video editing, and crosscut.
- Collaborate with research scientists and engineers to prototype, experiment, and scale generative AI techniques using software engineering best practices.
- Contribute to the design of datasets, evaluation methodologies, and infrastructure required for training and testing generative models.
- Analyze results to iterate on architectures, contribute to research publications, and help deploy successful research into GDM and Google products.
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 4 years of experience in designing, training, and evaluating deep generative models (e.g., Diffusion Models, Transformers, GANs) for media synthesis and manipulation (image, video, audio).
- 4 years of experience with experimentation, dataset curation, eval systems, and building ML pipelines.
- 4 years of experience with machine learning, computer vision, and deep learning.
Preferred qualifications:
- Master's or PhD degree in Computer Science, Machine Learning, Statistics, or a related field, or equivalent practical experience.
- Experience with multimodal learning, integrating video, audio, and text.
- Experience with video generation and editing models.
- Experience with Python and deep learning frameworks such as JAX, TensorFlow, or PyTorch.
- Knowledge of techniques for model optimization and efficient/low-latency inference suitable for real-time applications.
- Familiarity with real-time systems or media streaming technologies.