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Snapshot
At Google DeepMind, we've built a unique culture and work environment where long-term ambitious research can flourish. The multimodal team in Zurich investigates new architectures, approaches, and applications of foundational multimodal models. We are particularly interested in the interaction between these and data-centric aspects of training large-scale models. We believe there is a virtuous circle in which novel datasets enable novel models, and gaps in performance inspire new datasets.
About Us
Artificial Intelligence could be one of humanity’s most useful inventions. At Google DeepMind, we’re a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and ethics are the highest priority.
The Role
Research Scientists on the Multimodal team lead our efforts to advance architectural and data-centric approaches for multimodal models. This includes developing innovative data recognition, construction, optimization, and evaluation techniques to drive progress in the field. This work is intimately linked with the training of multimodal models, where each informs and refines the other.
We are looking for researchers who thrive in an interdisciplinary environment. Previous experience with multimodal, data centric research, or other parts of machine learning is valued.
Key responsibilities:
- Develop and evaluate methods for curating high-quality multimodal datasets, including collection, filtering, synthesis, annotation, and establishing evaluation metrics.
- Improve large-scale multimodal systems using data-centric approaches, such as developing novel datasets and tasks, optimizing data mixes, and refining loss functions.
- Design and build benchmarks and evaluation frameworks to assess multimodal models across diverse tasks and domains.
- Ensure inclusive, unbiased datasets and mitigate ethical risks associated with data collection and model development.
- Clearly communicate research findings and collaborate with Google teams for wider impact.
- Collaborate effectively to achieve ambitious research goals.
About You
In order to set you up for success as a Research Scientist at Google DeepMind, we look for the following skills and experience:
- PhD in machine learning, artificial intelligence or computer science.
- Research interests in data and novel dataset creation.
- Familiarity with experiment design principles.
- Experience with deep learning research.
- Strong coding and communication skills.
In addition, the following would be an advantage:
- Experience with multimodal modelling.
- A proven track record of publications in top-tier conferences.
- Understanding of data privacy and ethical considerations in data collection and use.
Application deadline: 4th February 5:00pm GMT
