Research Intern

Responsibilities

• Explore novel research directions in areas such as LLM reasoning, planning, tool use, multi-agent systems, or evaluation methodologies.
• Design and execute exploratory experiments to test new hypotheses and push the boundaries of what agentic systems can do.
• Build research prototypes that demonstrate new capabilities or insights, even if they are not immediately production-ready.
• Collaborate with the research team to document findings, analyze results, and iterate on ideas.
• Work toward publishing research outcomes in top-tier AI venues (NeurIPS, ICLR, ICML, ACL, etc.) or contributing to open-source efforts.
• Participate in team discussions, paper readings, and brainstorming sessions to shape the research roadmap.

Qualifications

• Currently pursuing or recently completed a PhD, Master's, or advanced undergraduate degree in machine learning, computer science, or a related field.
• Strong foundation in machine learning and natural language processing, with demonstrated interest in large language models or agentic AI systems.
• Proficiency in Python and familiarity with modern ML frameworks (e.g., PyTorch, JAX, or TensorFlow).
• Ability to design, implement, and analyze research experiments independently and collaboratively.
• Strong written and verbal communication skills, with a passion for sharing ideas and learning from others.
• Nice to have:
• Prior research experience or publications in AI, NLP, or related areas.
• Experience with open-weight models, fine-tuning, or reinforcement learning.
• Familiarity with agent frameworks, tool-use systems, or evaluation benchmarks.
• Interest in long-term research bets and comfort with ambiguity and exploration.