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13 часов назад

Research Intern (LLM Agents)

Формат работы
hybrid
Тип работы
fulltime
Грейд
trainee
Английский
b2
Страна
US
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

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TL;DR
Research Intern (LLM Agents) (AI/ML): Exploring and prototyping LLM agent systems across reasoning, planning, tool use, multi-agent coordination, and evaluation methodologies with an accent on exploratory experimentation and research prototyping. Focus on designing experiments, analyzing results, building novel agentic capabilities, and preparing outcomes for publication or open-source contribution.

Location: Palo Alto, United States; hybrid

Company

hirify.global conducts research and development focused on LLM agents and agentic AI systems.

What you will do

  • Explore research directions in LLM reasoning, planning, tool use, multi-agent systems, and evaluation methodologies.
  • Design and execute exploratory experiments to test hypotheses about agentic systems.
  • Build research prototypes that demonstrate new capabilities or insights.
  • Document findings, analyze results, and iterate on research ideas with scientists and engineers.
  • Work toward publishing research at AI venues such as NeurIPS, ICLR, ICML, and ACL, or contributing to open-source projects.
  • Participate in paper readings, discussions, and brainstorming sessions.

Requirements

  • 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 such as PyTorch, JAX, or TensorFlow.
  • Ability to independently and collaboratively design, implement, and analyze research experiments.
  • Strong written and verbal communication skills.

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 directions and comfort with ambiguity and exploration.

Culture & Benefits

  • Close collaboration with research scientists and engineers.
  • Mentorship, feedback, paper readings, and brainstorming sessions.
  • Freedom to pursue high-risk, high-reward research directions.
  • Opportunity to produce research prototypes, publications, and open-source contributions.

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