Snapshot
The Gemini Multilinguality team is responsible for improving the quality and language coverage of Gemini, and ensuring its responses are locally and culturally relevant. There are several ongoing workstreams:
- Improving quality of pretraining data and language coverage,
- Improving quality and language coverage of instruction-tuned models
- Enabling faster and more robust iteration on research via better evaluation benchmarks, autorater models, and novel uses for human data.
- Closely collaborating with Cloud, Search, Translate, Workspace, and others to bring the latest i18n research to Google users.
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
The Gemini Multilinguality team is seeking a Research Scientist to help us improve the quality and language coverage of Gemini. The successful candidate will have a strong track record of research in natural language processing, machine learning, and/or artificial intelligence, with a particular focus on multilingual modeling. Gemini is an ongoing effort from Google DeepMind to build state-of-the-art large language models trained on a massive multilingual and multimodal dataset. It can be used for a variety of tasks, including machine translation, text summarization, question answering, and dialogue generation.
Key responsibilities
- Conduct research on multilingual language models, with a focus on improving quality, language coverage, safety, and factuality.
- Develop new methods for scalable high-quality language expansion, data quality validation, and evaluation.
- Evaluate the performance of multilingual language models on a variety of tasks.
- Work with the Cloud, Search, and Workspace teams to integrate your research into models adapted for these surfaces.
- Collaborate closely with other researchers on the Gemini Multilinguality and adjacent teams.
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 Computer Science, or Machine Learning related field.
- Strong track record of research in multilingual language modeling.
- Experience with large-scale ML models and datasets.
In addition, the following would be an advantage:
- Proficient in Python.
- Excellent communication and presentation skills.
- A real passion for AI!
The US base salary range for this full-time position is between $136,000 - $245,000 + bonus + equity + benefits. Your recruiter can share more about the specific salary range for your targeted location during the hiring process.
At Google DeepMind, we value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact. We are committed to equal employment opportunities regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, or related condition (including breastfeeding) or any other basis as protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know.
Top Skills
What We Do
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.
Our long term aim is to solve intelligence, developing more general and capable problem-solving systems, known as artificial general intelligence (AGI).
Guided by safety and ethics, this invention could help society find answers to some of the world’s most pressing and fundamental scientific challenges.
We have a track record of breakthroughs in fundamental AI research, published in journals like Nature, Science, and more.Our programs have learned to diagnose eye diseases as effectively as the world’s top doctors, to save 30% of the energy used to keep data centres cool, and to predict the complex 3D shapes of proteins - which could one day transform how drugs are invented.
