Research Scientist, Earth AI
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Minimum qualifications:
- PhD in Computer Science, Artificial Intelligence, Machine Learning, Computer Vision, or equivalent practical experience.
- Experience in AI research and development, including in 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 (such as CVPR, ICCV, NeurIPS, ICML, ICLR, etc.).
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 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.
EarthAI is an exciting effort to build and bring together various powerful geospatial AI models with Gemini's agentic reasoning to help people, businesses and organizations address the planet's most critical needs. Earth AI expands on our recent Geospatial Reasoning effort and includes models that address multiple areas. This includes models to help improve urban planning and public health by providing a rich understanding of earth imagery, population dynamics and urban mobility. As well as detailed weather predictions, flood forecasting and wildfire detection.
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
- 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 significantly enhance geospatial reasoning capabilities, including advanced 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 and developments clearly and efficiently both internally and externally, verbally and in writing. Suggest and engage in team collaborations to meet ambitious research goals.
- Collaborate with cross-functional teams across Google to apply this technology to real-world problems. Your work will be influential both in the research community and also in products that promise to have a tremendous impact.
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Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.
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