Research Scientist

• Author research papers to share and generate impact of research results across function and in the research community.
• Architect scalable and reusable Machine Learning (ML) systems that create a multiplier effect, accelerating innovation across multiple teams.
• Own the full development lifecycle, translating research breakthroughs into production-ready models for integration into Platforms and Devices products.
• Oversee research into fundamental AI issues, developing novel solutions for long-context reasoning, Retrieval-Augmented Generation (RAG), and on-device model efficiency.
• Lead high-priority projects from research to launch, deploying technologies that directly shape future user experiences.

Minimum qualifications:

• PhD degree in Computer Science, a related field, or equivalent practical experience.
  
• 2 years of experience leading a research agenda.
  
• Experience in Generative AI, Generative AI Agent, Natural Language Processing, Large Language Model (LLM).
• One or more scientific publication submissions for conferences, journals, or public repositories (such as CVPR, ICCV, NeurIPS, ICML, ICLR, etc.).

Preferred qualifications:

• 2 years of coding experience.
  
• 1 year of experience leading research efforts and influencing other researchers.
  
• Experience in developing and deploying production-level models using Machine Learning, Deep Learning, LLMs, or Generative AI.
• Experience collaborating effectively with cross-functional, distributed teams, including Product Managers, Researchers, and engineers.
• Experience in a research or academic environment, with a track record of translating foundational research into practical applications.

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.

As a Research Scientist, you will lead high-priority projects from research to launch, deploying technologies that directly shape future user experiences. In this pivotal role, you'll collaborate closely with teams, placing you at the forefront of applied Artificial Intelligence (AI) innovation.

We are seeking passionate experts to provide solutions and guidance to product teams. This is a high-impact role, with the potential for your work to be featured at major events like Google I/O and Made by Google (MBG). Join us to drive the next wave of AI-powered innovation!

The Platforms and Devices team encompasses Google's various computing software platforms across environments (desktop, mobile, applications), as well as our first party devices and services that combine the best of Google AI, software, and hardware. Teams across this area research, design, and develop new technologies to make our user's interaction with computing faster and more seamless, building innovative experiences for our users around the world.

• PhD degree in Computer Science, a related field, or equivalent practical experience.
  
• 2 years of experience leading a research agenda.
  
• Experience in Generative AI, Generative AI Agent, Natural Language Processing, Large Language Model (LLM).
• One or more scientific publication submissions for conferences, journals, or public repositories (such as CVPR, ICCV, NeurIPS, ICML, ICLR, etc.).