Google Research is focused on advancing urban transportation by managing scientific breakthroughs in mobility. By leveraging the latest AI advancements in measurement, simulation, and optimization, the team translates research into core technologies that support solutions for Google Public Sector and Google Maps Platform. We build high-resolution digital twins of transportation systems to evaluate 'what-if' scenarios, develop ML-powered models for geospatial understanding, Origin-Destination travel demand estimation, and road safety models. Our mission is to equip transportation policymakers with the capabilities needed for data-driven decision-making, traffic management, and continuous monitoring, helping to build more efficient, safer, and resilient transportation systems.
Requirements
- Experience in spatio-temporal modeling,
- Excellent software engineering skills (e.g., C++, python, data processing, production backend development).
Responsibilities
- setup large-scale tests and deploy promising ideas quickly and broadly
- applying the latest theories to develop new and improved products, processes, or technologies
- creating experiments and prototyping implementations
- designing new architectures
- Author research papers to share and generate impact of research results across the team and in the research community.
- Define the data structure, framework, design, and evaluation metrics for research solution development and implementation under minimal guidance.
- Contribute to conducting experiments based on the research question.
Other
- PhD degree in Computer Science, a related field, or equivalent practical experience.
- One or more accepted scientific publication submissions for machine learning conferences or journals (e.g., NeurIPS, ICML, ICLR, KDD, AAAI).
- 2 years of experience in coding.
- 1 year of experience initiating, owning and delivering on research agendas.
- US base salary range for this full-time position is $141,000-$202,000 + bonus + equity + benefits.
