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.
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.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Bring a combination of engineering and research expertise to advance Gemini's multimodal understanding and generation capabilities.
- Design, implement, and scale state-of-the-art Large Language Models (LLM's) core image/video understanding capabilities.
- Drive end-to-end experimental workflows across pre-training and post-training.
- Build robust, scalable infra and data pipelines to support high-quality multimodal training and eval benchmarks.
- Partner closely with Research Scientists and Software engineers (SWEs) to transition cutting-edge research prototypes into production-ready foundation models, striking the right balance between rapid prototyping, maintainability, and generality.
Minimum qualifications:
- PhD degree in Computer Science, a related field, or equivalent practical experience.
- 2 years of experience leading a research agenda and influencing other researchers.
- 2 years of experience in an applied research setting.
- Experience in software engineering, including coding, code reviews, design discussions and reviews.
- Experience in Artificial Intelligence or Machine Learning.
Preferred qualifications:
- Experience with the GenAI techniques (e.g., LLMs, multimodal, large vision models) or with genAI-related concepts (e.g., evaluations, language modeling, computer vision).
- A proven track record of research or engineering achievements, such as publications in peer-reviewed conferences or journals.