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Research Engineer, Media Understanding

Google DeepMind

$215,000 - $250,000
Jun 10, 2025
Mountain View, CA, US
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Advancing the state-of-the-art research in Embedding/representation models in context of large language models to power Google products used by billions of people worldwide.

Requirements

  • Ph.D. in Computer Science or related quantitative field, or B.S./M.S. in Computer Science or related quantitative field with 5+ years of relevant experience.
  • Experience with core software engineering and applied implementations of AI.
  • Hands-on experience with Google-scale infrastructure, e.g. large scale data mining from various Google data stores, automation pipeline, client deployment across PAs.
  • Strong research experience and publication record in top tier conferences.
  • Experience with deep learning approaches.
  • Experience with multimodal models, large scale AI models and other key computer vision tasks.

Responsibilities

  • Conducting core research in the areas of computer vision, language understanding, multimodal models, large scale AI models and other key computer vision tasks.
  • Training and evaluating AI models for a variety of product use cases.
  • Researching, Implementing, and adapting state of the art deep learning approaches for Google’s use cases.
  • Collaborating closely with other GDM and partner teams to make progress towards building the most advanced embedding models.
  • Developing the next SOTA models for multimodal understanding.
  • Implementing research ideas, running experiments to evaluate improvements, and identifying new opportunities.

Other

  • Innovate and assess new machine learning models and techniques for pilot projects, quickly demonstrating viability and potential impact.
  • Transform successful prototypes into scalable solutions for wider integration within Google's products.
  • Collaborate with product teams to drive the implementation of research insights, fostering innovation and the development of new products.
  • A good team player who has demonstrated that they can work across teams given that image-text involves collaborating with both research and product teams.
  • Ph.D. in Computer Science or related quantitative field, or B.S./M.S. in Computer Science or related quantitative field with 5+ years of relevant experience.