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Mountain View, CA, USA; Kirkland, WA, USA; San Francisco, CA, USA; New York, NY, USA
Source: Google careers · View original posting
From Google's posting. “We” and “our” refer to the employer.
This role is dedicated to core modeling and post-training experience (e.g., deep learning, LLMs, and reinforcement learning). Because of this focus, applicants with primarily ML infrastructure (ML infra) backgrounds will likely find this is not the right profile for their skill set.
As a Research Engineer/Research Scientist, you will work on Agent Post-training and Personalization to build Consumer Agents. You will research, develop and scale foundational post-training methods that convert foundation models into autonomous, adaptive agents for consumers. Your focus centers on reinforcement learning, targeted data creation, and persistent context architectures so models retain user-specific state reliably over time and adapt to individual users.
Additionally, you will build training datasets and evaluation frameworks to test long-horizon reasoning, uncover failure modes, and measure agent reliability across complex workflows.
Artificial intelligence will be one of humanity’s most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority.
We are pushing the boundaries across multiple domains. Our global teams offer diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $262000 - $364000 (USD) + 25% bonus target + equity + benefits
Learn more about
benefits at Google.
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