Research Engineer, Media Understanding

Reposted 13 Days Ago
Be an Early Applicant
Mountain View, CA
215K-250K
Senior level
Artificial Intelligence
The Role
The Research Engineer will advance multimodal AI by developing models for understanding across media types, conducting research, and collaborating with teams.
Summary Generated by Built In

Research Engineer, Media Understanding- Multimodal Representation Models

Mountain View, CA

The Role

As part of the multimodal features team in Media Understanding at Google DeepMind, you will have the opportunity to advance the state-of-the-art research in Embedding/representation models in context of large language models. You'll be at the forefront of developing models that power Google products used by billions of people worldwide. Your work will directly impact how these products understand and interact with diverse media, including text, images, audio, and video.  This is a unique opportunity to shape the future of multimodal AI and its applications in a dynamic and impactful environment.

We are a team of research/software engineers, research scientists, and machine learning experts, working together to enable superhuman understanding of the visual world. We are aiming at training the most powerful omnimodal embedding model which can be used for retrieval and other agentic use cases in Google products. 

You'll be developing the next SOTA models for multimodal understanding. Your work will include researching new modeling techniques, implementing research ideas, running experiments to evaluate improvements, and identifying new opportunities.

Key Responsibilities

As a member of the media understanding team, you will be responsible for conducting core and applied research in computer vision and language understanding to support a multitude of Google products and use cases. Your job responsibilities will include:

  • 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.

About You

We are an applied research team that takes on challenging real-world problems and thrives on finding solutions in the presence of ambiguity. In order to set you up for success as a Research Engineer/Scientist at Google DeepMind, we look for the following skills and experience:

  • 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.
  • 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.
  • Conduct research to identify and address impactful problems inspired by current and future real-world needs. Investigate and develop novel solutions by studying related work, conducting experiments, and constructing prototypes and demonstrations.
  • Collaborate with product teams to drive the implementation of research insights, fostering innovation and the development of new products.

In addition, the following would be an advantage: 

  • Strong research experience and publication record in top tier conferences.
  • Experience with core software engineering and applied implementations of AI 
  • 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.
  • Hands-on experience with Google-scale infrastructure would be a plus, e.g. large scale data mining from various Google data stores. Automation pipeline. Client deployment across PAs.

The US base salary range for this full-time position is between $215,000 - $250,000 + bonus + equity + benefits. Your recruiter can share more about the specific salary range for your targeted location during the hiring process.

Application deadline: Friday, February 28th 2025

Note: In the event your application is successful and an offer of employment is made to you, any offer of employment will be conditional on the results of a background check, performed by a third party acting on our behalf. For more information on how we handle your data, please see our Applicant and Candidate Privacy Policy.

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.

 

Top Skills

Ai Models
Computer Vision
Deep Learning
Language Understanding
Machine Learning
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The Company
1,218 Employees
On-site Workplace
Year Founded: 2010

What We Do

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.

Our long term aim is to solve intelligence, developing more general and capable problem-solving systems, known as artificial general intelligence (AGI).

Guided by safety and ethics, this invention could help society find answers to some of the world’s most pressing and fundamental scientific challenges.

We have a track record of breakthroughs in fundamental AI research, published in journals like Nature, Science, and more.Our programs have learned to diagnose eye diseases as effectively as the world’s top doctors, to save 30% of the energy used to keep data centres cool, and to predict the complex 3D shapes of proteins - which could one day transform how drugs are invented.

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