Research Scientist, Agents for Science

About the Role

As a key member of the core team of research scientists and machine learning engineers at Ai2, you will drive the development of AI systems with deep reasoning capabilities with a focus on the huge breadth of skills necessary for scientific reasoning. In this role, you will lead foundational research to advance agentic systems, shape our strategic direction, and lay the groundwork for future innovations. You will also work towards long-term ambitious research goals, while identifying intermediate milestones.

Who You Are

You are a creative, hands-on AI researcher with a strong foundation in AI and reasoning. Passionate about pushing the boundaries of research and engineering, you seek to advance AI both scientifically and openly. You thrive in collaborative environments, take initiative, and are eager to contribute to Ai2’s impact-driven mission in a dynamic, fast-paced research setting. Skilled at translating complex concepts into concrete research goals and implementation steps, you define clear approaches, execute effectively, and communicate results with clarity. You leverage these skills to create real-world benefits for researchers and practitioners alike and are excited to help drive the development of the best-performing open AI model.

Responsibilities

• Contribute to Ai2’s open source research environment to innovate, study and advance the science of generative AI and agentic systems.
• Take a leading role in building artifacts and implementing software systems with real-world impact.
• Author and present high-quality scientific technical reports, papers, and presentations.
• Collaborate with and learn from team members across Ai2, including scientists and engineers.
• Mentor early-career researchers and interns on their projects.
• Develop collaborative relationships with relevant academic, industrial, government, and standards organizations.

Requirements

• A PhD focusing on machine learning, reasoning, natural language processing, or a related area, with expertise in one or more of the following: reinforcement learning, experimental methodology, language models, the science of deep learning, or efficient algorithms for deep learning. Curiosity about all of the above is a plus.
• The ability to own and pursue a research agenda to improve AI model reasoning capabilities.
• Enthusiasm for collaboration and teamwork on ambitious projects aligned with company goals.
• Experience leading a team to solve analytical problems (a plus).
• Contributions to open-source research libraries and an interest in continuing such work (a plus).