As an organization, Google maintains a portfolio of research projects driven by fundamental research, new product innovation, product contribution and infrastructure goals, while providing individuals and teams the freedom to emphasize specific types of work. As a Research Scientist, you'll setup large-scale tests and deploy promising ideas quickly and broadly, managing deadlines and deliverables while applying the latest theories to develop new and improved products, processes, or technologies. From creating experiments and prototyping implementations to designing new architectures, our research scientists work on real-world problems that span the breadth of computer science, such as machine (and deep) learning, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more.

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.

Research Scientist on the Sound team within Google DeepMind Frontier AI, focused on audio understanding, transformation, and generation. The role involves advancing research in sound understanding, joint audio-video generation, and audio editing, contributing to the next generation of generative AI technology.

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.

Responsibilities

• Improve quality of models for audio understanding and generation, including research on architectures, representations, training losses and paradigms, and test-time techniques for improved generation quality and efficiency.
• Unlock new audio capabilities in foundational models, both in pre-training and post-training data pipelines.
• Develop better evaluation methods (human evaluation, auto raters, automated metrics) to measure quality of open-ended audio tasks.
• Publish research at venues and contribute to Google DeepMind products.
• Collaborate across teams to advance research in sound understanding, joint audio-video generation, and audio editing.

Minimum qualifications:

• PhD degree in Computer Science, a related field, or equivalent practical experience.
• Experience with text, image, video, or audio generation.
• Experience in Artificial Intelligence or Machine Learning.
• Experience with Generative AI.

Preferred qualifications:

• PhD degree in Artificial Intelligence, Machine Learning, or a related technical field.
• One or more scientific publication submission(s) for conferences, journals, or public repositories.
• Experience developing, launching products, or technologies with Large Language Models (LLMs).