<h5>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.</h5> <h5><em>*Compensation dependent on current degree enrollment. <br></em>Research Intern, Undergrad: $94,320 (Annually) <br>Research Intern, Masters: $106,110 (Annually) <br>Research Intern, PhD: $140,000 (Annually) </h5> <p><strong>Who You Are:</strong></p> <p>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:</p> <ul> <li>Define and lead a high-impact research project.</li> <li>Train and release leading models.</li> <li>Collaborate with and learn from team members across Ai2.</li> <li>Build open-source software for the research community.</li> <li>Author scientific papers for publication in a high-profile conference or journal.</li> </ul> <p><strong>Ai2 Research Internship Information:</strong></p> <ul> <li><strong>Duration:</strong> 12 weeks</li> <li><strong>Start date:</strong> Flexible</li> <li><strong>Candidates:</strong> A PhD candidate or a master/undergraduate student with a strong research background</li> </ul> <p>We are currently hiring for start dates in 2027. If you have questions, feel free to reach out to <strong>olmo-careers@allenai.org</strong>. Please apply by <strong>January 8, 2027 at 11:00pm Pacific Time </strong>to be considered for our Spring/Summer 2027 internships. <strong> </strong></p> <p><strong>Who We Are: </strong></p> <p>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. </p> <p><strong>Your Next Challenge: </strong></p> <p>Why Open Ecosystem? We are building the foundation to foster years of open science and research on AI models.</p> <ul> <li>All interns are paired with one or more mentors from the Open Ecosystem team.</li> <li>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.</li> <li>Our pay is competitive, and visa sponsorship is available. </li> <li>We are committed to open science and support students freely publishing papers. Examples:</li> <ul> <li><a href="https://arxiv.org/abs/2512.13961">Olmo 3: Charting a path through the model flow to lead open-source AI</a></li> <li><a href="https://arxiv.org/abs/2601.10611">Molmo2: Open Weights and Data for Vision-Language Models with Video Understanding and Grounding</a></li> <li><a href="https://arxiv.org/abs/2511.19399">DR Tulu: Reinforcement Learning with Evolving Rubrics for Deep Research</a></li> <li><a href="https://arxiv.org/abs/2604.03444">OlmoHybrid: From Theory to Practice and Back</a></li> <li><a href="https://allenai.org/papers/olmocore3">OlmoCore 3: Supercharging Olmo-core for Efficient and Scalable MoE Training</a></li> </ul> </ul> <p>To see more about our current, future, and past interns, check out our<a href="http://allenai.org/internships.html"> internship page</a> on our website!</p> <p><strong>What You’ll Need:</strong></p> <p>Qualifications:</p> <ul> <li>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. </li> <li>Strong software engineering skills, especially with deep learning frameworks (e.g. PyTorch).</li> </ul> <p>Bonus qualifications:</p> <ul> <li>A strong publication record at AI-related venues, such as NeurIPS, ICLR, ICML, COLM, ACL, EMNLP.</li> <li>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.</li> <li>Contributions to open-source research libraries (e.g., PyTorch, Huggingface Transformers, olmo-core, AllenNLP).</li> </ul> <p><strong>Physical Demands and Work Environment:</strong></p> <p>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.</p> <ul> <li>Must be able to remain in a stationary position for long periods of time. </li> <li>The ability to communicate information and ideas so others will understand. Must be able to exchange accurate information in these situations. </li> <li>The ability to observe details at close range.</li> <li>Can work under deadlines.</li> </ul> <p&g