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Research Scientist, Google DeepMind

GoogleSingapore

Google will be prioritizing applicants who have a current right to work in Singapore, and do not require Google's sponsorship of a visa.


Minimum qualifications:

  • PhD in machine learning, computer science, or a related field.
  • 2 years of experience leading a research agenda.
  • Experience with large-scale distributed training and model parallelism.
  • One or more scientific publication submission(s) to machine learning conferences (e.g., ICML, NeurIPS, ACL).

Preferred qualifications:

  • Experience with deep learning frameworks (e.g., TensorFlow, PyTorch, JAX).
  • Deep understanding of Transformer architectures and their applications.
  • Familiarity with MoE, conditional computation, and other efficiency techniques.
  • Strong programming skills in Python and C++.
  • Excellent communication and collaboration skills.

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.

Responsibilities

  • Conduct cutting-edge research on efficient foundation model scaling.
  • Improve the efficiency of Transformer models for long sequences.
  • Develop and apply MoE techniques to enhance model capacity and performance.
  • Explore conditional computation methods to optimize resource allocation during training and inference.

Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google's Applicant and Candidate Privacy Policy.

Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy, Know your rights: workplace discrimination is illegal, Belonging at Google, and How we hire.

If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.

To all recruitment agencies: Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees, or any other organization location. Google is not responsible for any fees related to unsolicited resumes.

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