Research Internship at The Allen Institute for AI

Seattle, Washington, United States

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$94,320 – $140,000Compensation

InternshipExperience Level

InternshipJob Type

UnknownVisa

AI, Climate Science, ResearchIndustries

Requirements

Candidacy in a doctoral program in computer or computational/data science, applied math/statistics, physical sciences, or engineering (PhD candidate in Computer Science or Informatics, or in a climate-relevant physical science)
Relevant coursework and practical experience with machine learning
Strong skills in Python and collaborative software development in git
Good communication skills
Graduate-level coursework in atmospheric or climate science or some area of fluid dynamics (preferred)
Eager to learn new skills and work in a challenging environment
Ability to remain in a stationary position for long periods of time
Ability to communicate information

Responsibilities

Develop and apply novel AI methodologies to improve the generalization skill of ACE to unseen climates (such as those in the next 30 years) or to extend the capabilities, efficiency, and skill of AI-based downscaling for practical applications (e.g., assessing wildfire hazard or snowpack in a changing climate)
Work closely with a technical mentor on project design, coding, and testing

Skills

Key technologies and capabilities for this role

Machine LearningAIClimate ModelingComputer ScienceInformaticsPhysical ScienceDiffusion ModelsSuper-ResolutionGPU

Questions & Answers

Common questions about this position

What is the compensation for this research internship?

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

Is this internship remote or does it require on-site work?

Persons in these roles are expected to work from our offices in Seattle, with on-site requirements varying based on position and team. Contact your recruiter for specifics on this role.

What qualifications and skills are required for this internship?

Candidates must be a PhD candidate in Computer Science or Informatics, or in a climate-relevant physical science, with both relevant coursework and practical experience with machine learning required.

What is the company culture like at Ai2 for interns?

Interns work with world-class AI researchers and software engineers in a team-based, ambitious research environment focused on big breakthroughs in an exciting and interactive workplace, with a technical mentor for project design, coding, and testing.

What makes a strong application for this internship?

Strong candidates are PhD students in Computer Science, Informatics, or climate-relevant physical sciences with relevant coursework and practical machine learning experience, plus interest in AI for climate modeling; submit your completed application by January 4, 2026, for review and potential virtual interviews in January-February 2026.

The Allen Institute for AI

Advances AI through research and engineering

About The Allen Institute for AI

The Allen Institute for Artificial Intelligence (AI2) focuses on advancing artificial intelligence through research and engineering. It develops technologies that improve machine reasoning, common sense for AI, and language modeling. AI2 works on various projects, such as AllenNLP for natural language processing and EarthRanger for environmental monitoring. Unlike for-profit companies, AI2 operates as a non-profit, relying on grants and donations to fund its initiatives. This allows them to provide their research and tools to the public for free, promoting collaboration in the AI field. The goal of AI2 is to tackle significant scientific and engineering challenges to benefit society.

Seattle, WashingtonHeadquarters

2014Year Founded

N/ACompany Stage

AI & Machine LearningIndustries

201-500Employees

Benefits

Medical

401(k)

Visa Sponsorship

Time off

Catered meals & free snacks

Training & development

Tuition reimbursement

Remote & hybrid work options

Risks

Competition from OpenAI's QwQ-32B model may reduce AI2's market influence.

AI2's reliance on grants poses financial risks during economic downturns.

Open-source models may face intellectual property risks and misuse.

Differentiation

AI2 focuses on open-source models, promoting transparency and collaboration in AI development.

AI2's projects like AllenNLP and Semantic Scholar address diverse scientific and societal challenges.

AI2 operates as a non-profit, relying on grants and donations for funding.

Upsides

AI2's open-source models attract researchers, enhancing collaboration and innovation.

Tülu3 and OLMo-2 models position AI2 as leaders in open-source AI.

AI2's multimodal models meet the demand for integrated data processing in various fields.

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