Skip to content
The Allen Institute for AI

Research Internship, Open Ecosystem

Seattle, WA; SeattleUnited States
Intern · Research
POSTED 26 OCTVERIFIED 12H AGO
Apply Ask
Role
14 days opentrue age
Posted 26 Oct
Payin text
$94kposted
▲ +31% vs market median $72k
$69k$94k
Market p25–p75
$69k–$94k
The Allen Institute for AI p25–p75
$94kn=3
Seattle · n=13 · 365d to 6 Nov
CompanyThe Allen Institute for AI →
16open roles
Opened · 30d
+0
Closed · 30d
−0
3d of snapshots · 30d window
Market
12,247open · Intern Other
Opened · 7d
+8407% of open
All other
624,472open
All tracked boards · live 10 Nov · n=12,247
PyTorch

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 talented and motivated Research Interns to join our Open Ecosystem team, working on fully open foundation models like Olmo and Molmo . This internship offers a unique opportunity to contribute to cutting-edge research in AI in an exciting, fast-paced research environment. As a Research Intern, you have the opportunity to:

  • Define and lead a high-impact research project.
  • Train and release leading models.
  • Collaborate with and learn from team members across Ai2.
  • Build open-source software for the research community.
  • Author scientific papers for publication in a high-profile conference or journal.

Ai2 Research Internship Information

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

We are currently hiring for start dates in 2027. If you have questions, feel free to reach out to olmo-careers@allenai.org. ​​Please apply by January 8, 2027 at 11:00pm Pacific Time to be considered for our Spring/Summer 2027 internships.

Who We Are

We build the world’s most fully open AI models, working to advance new capabilities, improve performance and robustness, and make the building process more rigorous, transparent, and efficient. We deliver high-impact research and masterfully-engineered open-source tools to accelerate AI research around the world.

Your Next Challenge

Why Open Ecosystem? We are building the foundation to foster years of open science and research on AI models.

  • All interns are paired with one or more mentors from the Open Ecosystem team.
  • We encourage open collaboration on intern projects, even with researchers at external institutions. We have close ties to the University of Washington, only 1.5 miles away.
  • Our pay is competitive, and visa sponsorship is available.
  • We are committed to open science and support students freely publishing papers. Examples:
  • Olmo 3: Charting a path through the model flow to lead open-source AI
  • Molmo2: Open Weights and Data for Vision-Language Models with Video Understanding and Grounding
  • DR Tulu: Reinforcement Learning with Evolving Rubrics for Deep Research
  • OlmoHybrid: From Theory to Practice and Back
  • OlmoCore 3: Supercharging Olmo-core for Efficient and Scalable MoE Training

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

What You’ll Need

Qualifications:

  • Pursuing a doctoral degree in Computer Science or similar field with research experience in machine learning, natural language processing, language and vision, or related areas.
  • Strong software engineering skills, especially with deep learning frameworks (e.g. PyTorch).

Bonus qualifications:

  • A strong publication record at AI-related venues, such as NeurIPS, ICLR, ICML, COLM, ACL, EMNLP.
  • Experience in related areas of foundation model research like training dynamics, scaling laws, efficiency, data curation, post-training methods (e.g., SFT, DPO, RL), agentic training and infrastructure, and applications in scientific domains.
  • Contributions to open-source research libraries (e.g., PyTorch, Huggingface Transformers, olmo-core, AllenNLP).

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.

  • Must be able to remain in a stationary position for long periods of time.
  • The ability to communicate information and ideas so others will understand. Must be able to exchange accurate information in these situations.
Source · The Allen Institute for AIFirst seen 2 NovOriginal ↗