Research Scientist, Machine Learning, Geospatial AI

Minimum qualifications:

• 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).

Preferred qualifications:

• 2 years of experience in coding.
• 1 year of experience initiating, owning and delivering on research agendas.
• Experience in spatio-temporal modeling,
• Excellent software engineering skills (e.g., C++, python, data processing, production backend development).

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 MobilityAI team within 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.

Google Research is building the next generation of intelligent systems for all Google products. To achieve this, we’re working on projects that utilize the latest computer science techniques developed by skilled software developers and research scientists. Google Research teams collaborate closely with other teams across Google, maintaining the flexibility and versatility required to adapt new projects and foci that meet the demands of the world's fast-paced business needs.

The US base salary range for this full-time position is $141,000-$202,000 + 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 the team and in the research community. 
  
• Help in growing research business across teams by sharing research trends and best practices within the community. 
  
• Define the data structure, framework, design, and evaluation metrics for research solution development and implementation under minimal guidance. Identify timelines and obtain resources needed. 
  
• Identify new and upcoming research areas by interacting with potential external and internal collaborators. Help in developing long-term research strategy and plans to expand the impact of Google research with some guidance. 
  
• Contribute to conducting experiments based on the research question. Develop research prototypes or conduct simulations to further evaluate the impact of research, finalize hypotheses, and refine the research methodology under minimal guidance.