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Salary
≈ $157k – $300k per year (Estimated)
Location
In office (New York)
Seniority
Senior

Confirmed on the employer's own hiring board on Oct 22, 2026. First seen by Alion on Oct 21, 2026.

Overview
Company
Impact
Profile match
Google DeepMind is the artificial intelligence research and engineering division of Alphabet, formed in 2023 by merging the London laboratory founded in 2010 with the Google Brain team. It builds frontier foundation models such as the Gemini family, generative media systems including Veo and Imagen, and scientific tools like AlphaFold, whose protein structure predictions earned a share of the 2024 Nobel Prize in Chemistry. The unit pairs long-horizon research on reinforcement learning and general intelligence with product delivery across Google Search, Workspace, Android and Google Cloud.

About the job

As an organization, Google maintains a portfolio of research projects driven by fundamental research, new product innovation, product contribution and infrastructure goals, while providing individuals and teams the freedom to emphasize specific types of work. As a Research Scientist, you'll setup large-scale tests and deploy promising ideas quickly and broadly, managing deadlines and deliverables while applying the latest theories to develop new and improved products, processes, or technologies. From creating experiments and prototyping implementations to designing new architectures, our research scientists work on real-world problems that span the breadth of computer science, such as machine (and deep) learning, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more.

As a Research Scientist, you'll also actively contribute to the wider research community by sharing and publishing your findings, with ideas inspired by internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world.

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: $207000 - $300000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

  • Identify fundamental weaknesses in current agent capabilities and establish research roadmaps and technical strategies to systematically solve them.
  • Mentor, guide, and elevate junior scientists and engineers, fostering a culture of technical excellence and innovation.
  • Guide ambitious team collaborations, aligning efforts across Google DeepMind to execute on shared, high-impact research goals.
  • Report and present complex research breakthroughs clearly and efficiently. Act as a principal representative of our work internally and externally at global venues.
  • Build, lead, and maintain collaborations with key external research labs and leading individuals in the field.

Qualifications

Minimum qualifications:

  • PhD degree in Computer Science, a related field, or equivalent practical experience.
  • Experience with post-PhD academic or industry research in the field of artificial intelligence (AI).
  • One or more scientific publication submission(s) for conferences, journals, or public repositories (NIPS, ICML, ACL, CVPR, etc.).

Preferred qualifications:

  • Demonstrated experience in mentoring researchers and successfully translating fundamental AI research into major engineering systems or product applications.
  • Deep, authoritative expertise in scaling deep neural network architectures.
  • A real passion for AGI and shaping the future of AI safely and responsibly.
  • A proven track record of acting as a technical lead or principal investigator on complex, large-scale machine learning projects.
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