Research Scientist, Human-Centric Modeling

New York City, New York, US

DeepMind

Artificial intelligence could be one of humanity’s most useful inventions. We research and build safe artificial intelligence systems. We're committed to solving intelligence, to advance science...

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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 opportunities 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.

Snapshot

Members of the Human-centric Modeling group contribute broadly across DeepMind efforts including to the Gemini program and applied research for Google products. The Affective Computing subgroup works on socio-emotional understanding and generation tasks in audio-, visual- and audiovisual settings, primarily using large language models. Research includes, but is not limited to, better audio-visual representations for understanding emotional expressions, controllability of expressions in generated imagery/video/speech, conversational naturalness in dialog and TTS, emotion-aware reinforcement learning and agents, and safety mechanisms against harms like emotional manipulation and over-reliance.

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.

The role

Research Scientists at Google DeepMind lead our efforts in developing novel algorithmic architecture towards the end goal of solving and building Artificial General Intelligence.

In this role, responsibilities will include making key contributions into the latest research developed into the Gemini audio workstream, such as:

Key responsibilities

  • Data: Unlocking new multimodal affective capabilities in large models, both pre-training and post-training, focusing on audiovisual conversational settings.
  • Models: Improving quality of models for understanding and generation. This includes research to improve tokenizers, better techniques for generation quality, distill for on-device, and looking at joint audio and visual representations. 
  • Evals: Better evaluation methods (human, auto raters, automated metrics) to measure quality of open-ended tasks. 

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 in Computer Science, or Machine Learning related field.
  • Experience working with LLMs.
  • Audio or video understanding and/or generation experience.

In addition, the following would be an advantage: 

  • Proven track record of research and publications in some of the following areas: audio generation, video generation, LLMs
  • Proven experience of TensorFlow or similar ML frameworks (e.g. JAX)
  • Experience applying and productionizing state-of-the-art large audiovisual, language and/or multimodal research
  • Experience collaborating cross-function and with other researchers
  • A real passion for AI!

The US base salary range for this full-time position is between $136,000 - $245,000 + bonus + equity + benefits. Your recruiter can share more about the specific salary range for your targeted location during the hiring process.

 

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Tags: Architecture Computer Science Gemini JAX LLMs Machine Learning PhD Reinforcement Learning Research TensorFlow

Perks/benefits: Career development Equity / stock options Salary bonus

Region: North America
Country: United States

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