Google is looking to solve 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.
Requirements
- Experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript), including application of data structures and algorithms
- Experience in Machine Learning (Graph Convolutional Networks, Deep Neural Networks, Transformers etc.) or related fields.
- Contribution to research communities or efforts, including publishing papers at conferences (such as NeurIPS, ICML, CVPR, SIGGRAPH etc.).
- Experience in large language models or graph mining research.
- Experience in research leadership.
- Proven track record of publication history at machine learning (ML)/data mining conferences with emphasis on our research area (such as GNNs, geometric deep learning, etc.).
- PhD degree in Computer Science, a related field, or equivalent practical experience.
Responsibilities
- Integrate graph-structured data with foundation models and generative AI.
- Develop novel methods to improve model performance on challenging real world problem settings and working with product teams to get these models out to users.
- Run experiments and document research results for academic conferences.
- Educate Googlers about best practices for learning and reasoning over graph data.
- Develop new data mining pipelines and make improvements to the Graph Mining library as needed.
- 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.
- Create experiments and prototyping implementations to designing new architectures
Other
- 2 years of experience
- PhD degree in Computer Science, a related field, or equivalent practical experience.
- Contribution to research communities or efforts, including publishing papers at conferences
- Ability to work on real-world problems and collaborate with research programs at partner universities and technical institutes
- Commitment to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.
