Senior Staff Research Scientist, Google Cloud AI

Minimum qualifications:

• PhD degree in Computer Science, a related field, or equivalent practical experience.
  
• 6 years of experience with research agendas across multiple teams or projects.
  
• One or more scientific publication submission(s) for conferences, journals, or public repositories.
  
• Coding experience in Python, JavaScript, R, Java, or C++.
  

Preferred qualifications:

• 4 years of experience leading multiple research efforts and influencing research direction.
  
• 2 years of coding experience in Python, JavaScript, R, Java, or C++.
  

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.

The AI and Infrastructure team works on the world’s toughest problems, redefining what’s possible and the possible easy. We empower Google customers by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Googler Cloud customers, and billions of Google users worldwide. We’re at the center of amazing work at Google by being the “flywheel” that enables our advanced AI models, delivers computing power across global services, and offers platforms that developers use to build services.

In AI and Infrastructure, we shape the future of hyperscale computing by inventing and creating world-leading future technology, and drive global impact by contributing to Google infrastructure, from software to hardware (including building Vertex AI for Google Cloud). We work on complex technologies at a global scale with key players in the AI and systems space. Join a team of talented individuals who not only work together to keep data centers operating efficiently but also create a legacy of driving innovation by building some of the most complex systems technologies.

The US base salary range for this full-time position is $248,000-$349,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

• Author research papers to share and generate impact of research results across organization and in the research community. 
  
• Contribute to research growth by sharing research trends and best practices within the community by reviewing academic papers, serving on program committees and grant panels, speaking at Google events or research conferences, or organizing research conferences and visioning activities. 
  
• Deliver full projects by defining the data structure, framework, design, and evaluation metrics for research solution development and implementation. Identify timelines and obtain resources needed. 
  
• Identify new and upcoming research areas by interacting with potential external and internal collaborators. Own long-term research strategy and plans to expand the impact of Google research. 
  
• Identify undefined problems in existing technology and engage stakeholders and leaders to address them.