Research Engineer, Media Integrity

DeepMindMountain View, CA
3d

About The Position

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 ethics are the highest priority. 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. To succeed in this role, you will need to be passionate about advancing information literacy using machine learning and other computational techniques. You'll join an interdisciplinary team of domain experts, ML researchers, and engineers to research and build systems and tools to assess the trustworthiness of media (images, audio, and videos) on the internet. Relevant domains may include, but are not limited to, determining media authenticity, context discovery, and open source intelligence investigations. A public example of recent work is Backstory.

Requirements

  • Master’s degree in Computer Science, Electrical Engineering, Science, or Mathematics, or equivalent experience.
  • Applied experience with machine learning, preferably modern deep learning techniques (e.g., Transformers, Diffusion, LLMs).
  • Programming experience.
  • Quantitative skills in math and statistics.
  • Experience exploring, analysing and visualising data.

Nice To Haves

  • Experience optimising large-scale training and fine-tuning large models.
  • Experience working with large and noisy datasets.
  • Experience collaborating across fields.
  • Expertise in computer vision or natural language understanding.

Responsibilities

  • Plan and perform rapid prototyping of machine learning techniques applied to determining authenticity of media information.
  • Undertake exploratory analysis to inform experimentation and research directions.
  • Engage with product teams to drive the development of our research.
  • Implement tools, libraries, and frameworks to speed up and enable new research.
  • Report and present research findings, software developments, experimental results, and data analysis clearly and efficiently.
  • Collaborate with internal and external scientific domain experts.
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