Google
Overview
Research Scientist, Earth AI role at Google. This position involves designing and implementing large-scale geospatial AI research, applying the latest theories to real-world problems, and contributing to the broader research community. About the Job
Google maintains a portfolio of research projects driven by fundamental research, new product innovation, product contribution and infrastructure goals. Researchers set up large-scale tests, deploy promising ideas quickly, and manage deadlines and deliverables while developing new architectures. Work spans machine learning, data mining, natural language processing, and related areas, with applications to geospatial data and Earth AI initiatives. Earth AI Focus
EarthAI brings together geospatial AI models and agentic reasoning to address critical needs. Projects include improving urban planning, public health with geospatial insights, weather predictions, flood forecasting, and wildfire detection. Responsibilities
Design and implement experiments, and evaluate algorithms and data curation for multi-modal generative AI over geospatial data like satellite imagery, street-level data, population, and environmental signals. Train and tune Gemini models and agents to enhance geospatial reasoning capabilities, including task understanding, planning, and multi-step execution in geographical contexts. Establish benchmarks and publish research to demonstrate the credibility of Google's geospatial models. Report and present research findings clearly and efficiently, internally and externally, and engage in team collaborations to meet ambitious research goals. Collaborate with cross-functional teams across Google to apply geospatial AI to real-world problems and influence both research and product directions. Qualifications
Minimum qualifications:
PhD in Computer Science, Artificial Intelligence, Machine Learning, Computer Vision, or equivalent practical experience. Experience in AI research and development, including generative AI. Experience in Python and machine learning frameworks (e.g., Jax, TensorFlow, PyTorch). One or more accepted scientific publication submissions for conferences, journals, or public repositories (e.g., CVPR, ICCV, NeurIPS, ICML, ICLR). Preferred qualifications:
Experience with geospatial data (e.g., satellite imagery, GIS). Experience in large-scale training of multimodal generative models. Experience in building multi-agent systems. Understanding of large language models (LLMs) and their application to agentic systems. Ability to lead a research project from conception to a successful outcome. Compensation and Benefits
The US base salary range for this full-time position is $141,000-$202,000 plus bonus, equity, and benefits. Salary ranges are determined by role, level, and location; the recruiter can share the specific range for your location. Compensation details reflect base salary and do not include bonus, equity, or benefits. Information about benefits is available from Google. EEO and Accommodations
Google is an equal opportunity employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, or veteran status. We consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you require accommodations during the application process, please let us know via our Accommodations for Applicants form. Applicants in San Francisco: Qualified applications with arrest or conviction records will be considered in accordance with the San Francisco Fair Chance Ordinance and the California Fair Chance Act. By applying, you may share your preferred working location: Mountain View, CA, USA; San Francisco, CA, USA.
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Research Scientist, Earth AI role at Google. This position involves designing and implementing large-scale geospatial AI research, applying the latest theories to real-world problems, and contributing to the broader research community. About the Job
Google maintains a portfolio of research projects driven by fundamental research, new product innovation, product contribution and infrastructure goals. Researchers set up large-scale tests, deploy promising ideas quickly, and manage deadlines and deliverables while developing new architectures. Work spans machine learning, data mining, natural language processing, and related areas, with applications to geospatial data and Earth AI initiatives. Earth AI Focus
EarthAI brings together geospatial AI models and agentic reasoning to address critical needs. Projects include improving urban planning, public health with geospatial insights, weather predictions, flood forecasting, and wildfire detection. Responsibilities
Design and implement experiments, and evaluate algorithms and data curation for multi-modal generative AI over geospatial data like satellite imagery, street-level data, population, and environmental signals. Train and tune Gemini models and agents to enhance geospatial reasoning capabilities, including task understanding, planning, and multi-step execution in geographical contexts. Establish benchmarks and publish research to demonstrate the credibility of Google's geospatial models. Report and present research findings clearly and efficiently, internally and externally, and engage in team collaborations to meet ambitious research goals. Collaborate with cross-functional teams across Google to apply geospatial AI to real-world problems and influence both research and product directions. Qualifications
Minimum qualifications:
PhD in Computer Science, Artificial Intelligence, Machine Learning, Computer Vision, or equivalent practical experience. Experience in AI research and development, including generative AI. Experience in Python and machine learning frameworks (e.g., Jax, TensorFlow, PyTorch). One or more accepted scientific publication submissions for conferences, journals, or public repositories (e.g., CVPR, ICCV, NeurIPS, ICML, ICLR). Preferred qualifications:
Experience with geospatial data (e.g., satellite imagery, GIS). Experience in large-scale training of multimodal generative models. Experience in building multi-agent systems. Understanding of large language models (LLMs) and their application to agentic systems. Ability to lead a research project from conception to a successful outcome. Compensation and Benefits
The US base salary range for this full-time position is $141,000-$202,000 plus bonus, equity, and benefits. Salary ranges are determined by role, level, and location; the recruiter can share the specific range for your location. Compensation details reflect base salary and do not include bonus, equity, or benefits. Information about benefits is available from Google. EEO and Accommodations
Google is an equal opportunity employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, or veteran status. We consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you require accommodations during the application process, please let us know via our Accommodations for Applicants form. Applicants in San Francisco: Qualified applications with arrest or conviction records will be considered in accordance with the San Francisco Fair Chance Ordinance and the California Fair Chance Act. By applying, you may share your preferred working location: Mountain View, CA, USA; San Francisco, CA, USA.
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