Research Engineer, Media Integrity

DeepMind • Mountain View, CA

2d

About The Position

At Google DeepMind, our research team is dedicated to tackling the most complex challenges in online information quality. We strive to advance the state of the art by developing innovative solutions to detect manipulated media and misleading narratives, ensuring the integrity of digital discourse. A prominent example of our scientific discovery is Backstory. Our interdisciplinary work spans provenance analysis and the creation of tools for AI-assisted information literacy, leveraging our technologies for the widespread public benefit of a safer online environment. We thrive in a supportive environment that encourages rapid prototyping and iteration, driving our research achievements directly into Google’s flagship models, including Gemini.
About us
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.
The role
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.

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.
• PhD/Master’s degree in Computer Science, AI, ML, or equivalent practical experience.
• At least 2 years of relevant experience developing machine learning models.
• Experience in software development using Python and deep learning frameworks (e.g., Jax, TensorFlow, PyTorch), with a proven track record of building high-quality research prototypes and systems.
• Quantitative skills in math and statistics.
• Experience exploring, analysing and visualising data.

Nice To Haves

• Experience in multimodal learning, including the training and deployment of large-scale models.
• Experience developing AI agents.
• Experience with Large Language Models, prompt engineering, few-shot learning, post-training techniques, and evaluations.
• A proven track record of research or engineering achievements, such as publications in peer-reviewed conferences or journals.

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.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level