Research Internship, OlmoEarth

Persons in these roles are expected to work from our offices in Seattle. On-site requirements vary based on position and team. If you have questions about on-site work arrangements for this role, please ask your recruiter.

* Compensation dependent on current degree enrollment.
Research Intern, Undergrad: $94,320 (Annually)
Research Intern, Masters: $106,110 (Annually)
Research Intern, PhD: $140,000 (Annually)

Who You Are:

Ai2 is seeking a passionate early-career AI researcher to join our team working on foundation modeling of Earth observation data. This internship offers a unique opportunity to work on impactful research at the intersection of foundation models and some of the biggest challenges facing our planet. We work across many areas including environmental monitoring, sustainability, wildfire resilience, food security, conservation, and beyond.

As a Research Intern, you have the opportunity to:

• Define and lead a high-impact research project using spatio-temporal Earth observation data.
• Train, evaluate, and contribute to the next generation of Olmo Earth.
• Build open-source software, tools, and benchmarks that enable environmental and humanitarian applications.
• Author scientific papers and technical reports for high-profile conferences or journals.

Ai2 Internship Information:

• Duration: 12 weeks
• Start date:
  Flexible
• Candidates: A PhD candidate or a master/undergraduate student with a strong research background.

Please apply by January 4, 2026 at 11:00pm Pacific Time to be considered for our Summer 2026 internships. We plan to contact a short list of applicants by the end of January 2026.

To see more about our current, future, and past interns, check out our internship page on our website!

Who We Are:

We are a team of researchers and engineers building foundation models for Earth and making them broadly accessible for impactful applications. We recently released Olmo Earth, a spatio-temporal foundation model for Earth observation data that establishes a new Pareto frontier in computational efficiency and accuracy (https://(Use the "Apply for this Job" box below).). We also released a new platform that enables organizations without AI or engineering resources to leverage this technology for environmental and humanitarian applications: .

At Ai2, you will be working with world-class AI researchers and talented Olmo Earth software engineers. We perform team-based, ambitious research, with a mandate to strive for big breakthroughs-not just incremental progress-in an exciting and interactive workplace.

Your Next Challenge:

We are building the foundation to support years of open science and research on Earth intelligence and planetary-scale modeling.

• All interns are paired with a mentor from the Olmo Earth research team and participate directly in Ai2's groundbreaking work.
• We encourage open collaboration on intern projects, including with researchers and practitioners at external institutions, NGOs, and partner organizations.
• We are committed to open science and place no restrictions on publications based on internships.

We are passionate about building open AI for good and using foundation models to tackle real-world environmental and humanitarian challenges.

What You'll Need:

• Students (Ph.D., masters, or exceptional undergraduates) with a strong academic record.
• Experience and/or knowledge of modern deep learning (LLMs, vision transformers, SSL).
• Experience with foundation models (pretraining, fine tuning, etc.).
• Interest in applying AI to address global challenges like wildfire and food insecurity.
• Expertise in Python and modern ML engineering stack (Git Hub, CI, etc).

Bonus:

• Successful past internships or full time employment in a technical role.
• Highly proactive and self-motivated.
• Experience with satellite imagery.
• Demonstrated contributions to open source projects.
• Experience with working with large pretraining datasets (hundred TB → PB) datasets.
• Experience training large models on multi-node GPUs.
• Experience working with partners in the field on ML for EO.

Physical Demands and Work Environment:

The physical demands described here are representative of those that must be met by an employee to successfully perform the…