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Snapshot

Accelerate research in strategic projects that enable trustworthy, robust and reliable machine learning with a group of research scientists and engineers on a mission-driven team. Together, you will apply ML and other computational techniques to a wide range of challenging problems. A public example of recent work is SynthID, and we are actively pursuing other exciting projects across many disciplines. 

About Us

We’re a dedicated scientific community, committed to “solving intelligence” and ensuring our technology is used for widespread public benefit.

We’ve built a supportive and inclusive environment where collaboration is encouraged and learning is shared freely. We don’t set limits based on what others think is possible or impossible. We drive ourselves and inspire each other to push boundaries and achieve ambitious goals.

The Role

As a Research Scientist in Strategic Initiatives, you will use your machine learning expertise to collaborate with domain experts and other machine learning scientists within our strategic initiatives programs. Domains may include, but are not limited to, machine learning robustness, the provenance of synthetic media, and the trustworthiness of data.

Key responsibilities:

• Engage with existing research efforts in the Strategic Initiatives Program to solve key challenges using your broad machine learning experience.
• Collaborate with researchers and machine learning engineers to identify and develop novel machine learning approaches to solve meaningful strategic problems.
• Report and present research findings and developments (including status and results) clearly and efficiently both internally and externally, verbally and in writing.
• Suggest and engage in team collaborations to meet research goals for the wider science programme.

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 demonstrating significant advances in machine learning or equivalent practical experience.
• Passion for accelerating the development of safe machine learning using innovative technologies.
• Programming experience.
• Quantitative skills in maths and statistics.
• Experience with common scripting languages and pipelining tools.

In addition, the following would be an advantage: 

• Experience in applying machine learning techniques to problems surrounding robust and trustworthy deployments of models.
• Experience with GenAI audio or video models.
• Demonstrated success in delivering high quality research impact.
• Experience with adversarial robustness, data influence or watermarking.
• A real passion for AI!

In assessing technical backgrounds, we will take a holistic view of the mix of scientific, machine learning, and computational experience. We do not expect you to be an expert in all fields simultaneously.

Closing date: Friday, 14th February 5:00pm GMT