Research Scientist, Strategic Initiatives, Multimedia ML

TLDR

Collaborate with domain experts and machine learning scientists to tackle strategic challenges in multimedia GenAI and data trustworthiness through research and novel approaches.

Snapshot

Accelerate research in strategic projects that enable trustworthy 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 exciting projects in the space of data trustworthiness.

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, multimedia GenAI pre-training, post-training and inference with an emphasis on data influence and trustworthiness.

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.
  • Engage with product teams to drive the deployment of our research.
  • 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.
  • Demonstrated success in delivering high quality research impact.
  • Experience with GenAI models for multimodal (image, audio, video) across the training and inference lifecycle.
  • Experience with data influence, similarity-based embeddings and auto-raters.
  • Programming experience across common scripting languages and pipelining tools.
  • A real passion for AI!

In addition, the following would be an advantage: 

  • Experience in robust and large-scale deployment and inference of those models.

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.

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 opportunity 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.

DeepMind develops advanced artificial intelligence systems that push the boundaries of what's possible. We cater to a diverse range of scientific communities and industries, focusing on creating AI technologies that can tackle significant global challenges and drive public benefit. Our distinctive approach combines deep learning and reinforcement learning with insights from neuroscience, fostering a culture of innovative research and collaboration.

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