AI Research and Development Lead

The role of the Advanced AI Researcher will be to develop and drive an agenda around state-of-the-art methods for AI generative media models, with a particular focus on culturally-adapted image and video generation.

At Google DeepMind, we've built a unique culture and work environment where long-term ambitious research can flourish. Our special interdisciplinary team combines the best techniques from deep learning, reinforcement learning, and systems neuroscience to build general-purpose learning algorithms. We have already made a number of high-profile breakthroughs towards building artificial general intelligence (AGI), and we have all the ingredients in place to make further significant progress over the coming year.

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 responsibility are the highest priority.

Our Advanced AI Researchers lead our efforts in developing novel tools, infrastructure, and algorithms towards the end goal of solving and building Artificial General Intelligence. They have a keen sense of strategically important and impactful problems. They should excel in a research driven culture, be comfortable diving deep into the details, yet be able to step back and communicate both the strategic and immediate implications on priorities.

Having pioneered research in the world's leading academic and industrial labs, PhDs, post-docs, or professorships, our researchers join us to work collaboratively within and across research fields. They are expected to work with teams on large scale AI, and develop solutions to fundamental questions in machine learning and AI.

Drawing on expertise from a variety of disciplines including deep learning, computer vision, language modeling, and advanced generative architectures, our Advanced AI Researchers are at the forefront of groundbreaking research.

1. Set the technical vision and strategic direction for the team's research and development efforts towards novel research that improves the state-of-the-art in Multimodal Generative AI, with a particular emphasis on culturally-adapted image and video synthesis.
2. Lead, mentor, and grow a high-performing team, fostering a culture of innovation, collaboration, and technical excellence.
3. Drive the end-to-end execution of complex research projects, from rapid-prototyping of novel datasets and methods to developing principled, scalable techniques.
4. Act as the primary technical point of contact, representing the team's work and influencing stakeholders across our organization and external partners.
5. Work in collaboration with our Responsibility and Governance teams to ensure our advances in intelligence are developed ethically and provide broad benefits to humanity.

We are seeking a researcher who thrives in ambiguity and is adept at navigating the uncertainty of research. You are skilled at guiding a team to invent novel solutions, pivot when ideas don't work out, and maintain momentum.

In order to set you up for success as a Research Scientist Lead at Google DeepMind, we look for the following skills and experience:

1. A PhD in Computer Science, Artificial Intelligence, Machine Learning, Computer Vision, or equivalent practical experience.
2. Significant experience building and leading world-class research and engineering teams.
3. Proven experience in deep learning research and development, particularly in generative AI and related to image and video synthesis.
4. Exceptional engineering skills in Python and deep learning frameworks (e.g., Jax, TensorFlow, PyTorch), with a track record of building high-quality systems.
5. A strong publication record at top-tier machine learning, computer vision, and graphics conferences (e.g., NeurIPS, ICLR, ICML, SIGGRAPH, CVPR, ICCV).
6. Excellent communication, interpersonal and leadership skills.
7. A passion for our mission and excited about AI and its potential for scientific and real-world impact.

Additionally, demonstrated experience in large-scale training of multimodal generative models would be an advantage.