Staff ML Software Engineer, Earth AI

Minimum qualifications:

• Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience.
• 8 years of experience in software development.
• 5 years of experience testing and launching software products.
• 3 years of experience with software design and architecture.
• Experience in Python and machine learning frameworks (e.g., Jax, TensorFlow, PyTorch).

Preferred qualifications:

• Master's degree or PhD in Computer Science, Geoinformation Science, or a related field, with a focus on machine learning, computer vision.
• Deep understanding and experience with Large Language Models (LLMs) and their application to agentic systems.
• Proven track record of leading a team of engineers, with experience mentoring and growing talent.
• Deep technical knowledge of multi-modal machine learning, geospatial reasoning, knowledge graphs.
• A history of designing and shipping complex, large-scale technical projects from end-to-end.
• One or more accepted scientific publication submissions for conferences, journals, or public repositories (such as CVPR, ICCV, NeurIPS, ICML, ICLR, etc.).

About the job

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

As a Staff ML Engineer, you will be the anchor for a high-impact team at Google Research focused on geospatial reasoning. In this role, you will help develop and drive an agenda around state-of-the-art methods for AI generative models to solve complex geospatial problems. You will architect, design, and oversee the experimentation and development of complex, large-scale systems that fuse geospatial data modalities (e.g., satellite imagery, street-level data, population data, knowledge graphs) to enable advanced geospatial reasoning. This role is not just about building; it's about leading. You will be responsible for guiding junior and mid-level engineers, making critical architectural decisions, and ensuring the team's work is aligned with Google's broader AI and research strategy.

Google Research addresses challenges that define the technology of today and tomorrow. From conducting fundamental research to influencing product development, our research teams have the opportunity to impact technology used by billions of people every day.

Our teams aspire to make discoveries that impact everyone, and core to our approach is sharing our research and tools to fuel progress in the field -- we publish regularly in academic journals, release projects as open source, and apply research to Google products.

The US base salary range for this full-time position is $197,000-$291,000 + 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

• Set the research and technical vision and strategic direction for the team's research and development efforts towards state-of-the-art models in Generative AI for complex global geospatial problems. Partner closely with research scientists and product managers to define the long-term technical roadmap for the team. 
• Own the technical architecture for large-scale geospatial reasoning systems. Design resilient, scalable, and efficient systems that can handle petabytes of data and serve sophisticated reasoning models. 
• Work on the most ambiguous and challenging technical problems in the field, this includes innovating new data representations, designing novel model architectures for spatial reasoning, and optimizing performance on cutting-edge hardware (TPUs, GPUs).
• Act as the primary technical point of contact for external teams, collaborating with other Google organizations to integrate and deploy your team's research.