Lead Research Engineer, Earth System

Persons in these roles are expected to spend part of their time on-site in our Seattle offices and may occasionally work remotely from their home in the Greater Seattle area. On-site requirements vary based on position and team. If you have questions about Hybrid work arrangements for this role, please ask your recruiter.

Our base salary range is $200,800 - $301,320, and in addition we have generous bonus plans to provide a competitive compensation package. 

Who You Are:

We are looking for a Lead Research Engineer who is passionate about pushing the boundaries of geospatial intelligence. 

Who We Are: 

We are building Earth-System (https://allenai.org/earth-system), a new platform for large-scale planetary intelligence. Our mission is to tackle some of the world’s most complex environmental challenges—spanning climate change, sustainability, food security, humanitarian aid, and conservation—through AI. This platform will combine highly mixed-modality geospatial foundation models with the infrastructure to fine-tune and deploy them at scale. Our models analyze many different types of planetary data including satellite imagery, elevation maps, super-resolution weather forecasts, and other geospatial data sources for tasks such as ecosystem mapping, forest loss driver classification, carbon sequestration, wildfire risk mapping, and land cover change detection.

Your Next Challenge:

We face major open research and engineering challenges that require deep expertise and execution at scale:

• Research Challenges: Advancing foundation models for geospatial intelligence; addressing domain adaptation, low-resource settings, and high-impact decision-making; and minimizing the cost of annotating high-quality, large-scale geospatial datasets
• Engineering Challenges: Scaling model training and inference responsibly, efficiently, and cost-effectively—particularly for users with limited compute or edge deployments beyond WiFi range.
• Product & Deployment: Building robust AI-first tools that enable scientists, policymakers, and conservationists to generate actionable intelligence with minimal friction.

You’ll thrive in this role if you:

• Move fluidly between AI research and production engineering.
• Are deeply experienced in one or several areas in foundational machine learning research, and  production-scale deployment.
• Operate with autonomy and a bias toward action, iterating quickly while ensuring long-term sustainability.
• Enjoy working in a highly collaborative environment.

You will join a rapidly growing team of scientists, engineers, and AI practitioners dedicated to leveraging AI for social good at scale. We operate across research, engineering, and product development, shipping models that are already industry leading in climate, geospatial intelligence, maritime AI, and other domains. 

We are:

• Strong advocates of responsible and ethical AI.
• Committed to open-source and publishing our work.
• Focused on building AI that empowers users beyond the lab, making a tangible impact.

If you want to build scalable, high-impact AI that helps the world understand and respond to planetary change, we’d love to hear from you.

What You’ll Need:

Minimum qualifications:

• Bachelor’s degree in Computer Science, ML/AI, or relevant technical field, or equivalent practical experience.
• Experience building, scaling, and optimizing enterprise-grade ML/AI systems
• Experience coding in Python, C/C++, or other similar languages
• Experience communicating AI research and development to audiences with different (non-technical) backgrounds
• 5+ years experience working in ML 
• Expertise in geospatial AI, such as remote sensing and/or ML for geospatial trajectories

Preferred qualifications:

• Ph.D., research background in ML/AI in CS or AI, or relevant technical field
• Experience in large-scale cloud infrastructure
• Experience with large scale machine learning infrastructure deployments 

Physical Demands and Work Environment:

The physical demands described here are representative of those that must be met by a team member to successfully perform the essential functions of this position. Reasonable accommodations may be made to enable individuals with disabilities to perform the functions.