Google
Job Title
Research Scientist, Earth AI
at
Google .
Location & Fair Chance Applicants in San Francisco will be considered in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act.
Note: You may select your preferred working location:
Mountain View, CA, USA
or
San Francisco, CA, USA .
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 publications in 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.
About The Job As part of Google’s research portfolio, the Earth AI team leverages geospatial AI models combined with Gemini’s agentic reasoning to tackle critical global challenges. You will design large-scale experiments, deploy solutions quickly, and contribute to real-world products. Your work spans machine learning, data mining, NLP, hardware performance, and core search technologies.
Earth AI focuses on models for urban planning, public health, weather prediction, flood forecasting, and wildfire detection, building on recent Geospatial Reasoning efforts.
The position involves collaborating closely with teams across Google, adapting projects to fast-paced business needs.
Salary & Benefits The US base salary range for this full-time position is $141,000–$202,000 plus bonus, equity, and benefits. Compensation depends on role, level, location, and experience. Salary ranges reflect base only; bonus, equity, and benefits are additional.
Responsibilities
Design and implement experiments, evaluate algorithms, and curate data for multimodal generative AI over geospatial data such as satellite imagery, street-level data, population, and environmental signals.
Train and tune Gemini models and agents to enhance geospatial reasoning, including task understanding, planning, and multi-step execution in geographic contexts.
Establish benchmarks and publish research to demonstrate credibility of Google’s geospatial models.
Report and present research findings clearly and efficiently, both internally and externally, in writing and verbally.
Collaborate with cross‑functional teams to apply the technology to real-world problems, influencing the research community and products.
Equal Employment Opportunity Google is proud to be an equal‑opportunity workplace and an affirmative action employer. We are committed 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. We also consider qualified applicants regardless of criminal history, consistent with legal requirements. Please let us know if you need accommodations by completing our Accommodations for Applicants form.
Seniority Level Not Applicable
Employment Type Full‑time
Job Function Information Technology and Engineering
Industries Information Services and Technology, Information and Internet
#J-18808-Ljbffr
at
Google .
Location & Fair Chance Applicants in San Francisco will be considered in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act.
Note: You may select your preferred working location:
Mountain View, CA, USA
or
San Francisco, CA, USA .
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 publications in 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.
About The Job As part of Google’s research portfolio, the Earth AI team leverages geospatial AI models combined with Gemini’s agentic reasoning to tackle critical global challenges. You will design large-scale experiments, deploy solutions quickly, and contribute to real-world products. Your work spans machine learning, data mining, NLP, hardware performance, and core search technologies.
Earth AI focuses on models for urban planning, public health, weather prediction, flood forecasting, and wildfire detection, building on recent Geospatial Reasoning efforts.
The position involves collaborating closely with teams across Google, adapting projects to fast-paced business needs.
Salary & Benefits The US base salary range for this full-time position is $141,000–$202,000 plus bonus, equity, and benefits. Compensation depends on role, level, location, and experience. Salary ranges reflect base only; bonus, equity, and benefits are additional.
Responsibilities
Design and implement experiments, evaluate algorithms, and curate data for multimodal generative AI over geospatial data such as satellite imagery, street-level data, population, and environmental signals.
Train and tune Gemini models and agents to enhance geospatial reasoning, including task understanding, planning, and multi-step execution in geographic contexts.
Establish benchmarks and publish research to demonstrate credibility of Google’s geospatial models.
Report and present research findings clearly and efficiently, both internally and externally, in writing and verbally.
Collaborate with cross‑functional teams to apply the technology to real-world problems, influencing the research community and products.
Equal Employment Opportunity Google is proud to be an equal‑opportunity workplace and an affirmative action employer. We are committed 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. We also consider qualified applicants regardless of criminal history, consistent with legal requirements. Please let us know if you need accommodations by completing our Accommodations for Applicants form.
Seniority Level Not Applicable
Employment Type Full‑time
Job Function Information Technology and Engineering
Industries Information Services and Technology, Information and Internet
#J-18808-Ljbffr