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7 часов назад

Generative AI Research Intern (AI)

Формат работы
onsite
Тип работы
fulltime
Грейд
trainee
Английский
b2
Страна
Taiwan
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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TL;DR

Generative AI Research Intern (AI/ML): Advancing Large Language Models (LLMs), Vision-Language Models (VLMs), and AI agents with an accent on post-training, multimodal intelligence, and autonomous agentic systems. Focus on building agentic AI systems, implementing SFT/RLHF techniques, and bridging frontier research with production impact.

Location: Taipei, Taiwan

Company

hirify.global is a software-as-a-service (SaaS) company that uses artificial intelligence to power business decision-making.

What you will do

  • Research and build agentic AI systems focusing on reasoning, planning, and multi-agent collaboration.
  • Advance post-training techniques including SFT, RLHF, and preference optimization to improve model alignment.
  • Optimize performance, efficiency, and scalability of foundation models during training and inference.
  • Design rigorous evaluations and benchmarks for AI agents in real-world scenarios.
  • Collaborate with cross-functional teams to integrate research findings into production applications.
  • Track frontier research and publish findings at top AI/ML conferences.

Requirements

  • Master's or Ph.D. in Computer Science, Electrical Engineering, Mathematics, or a related field.
  • Expertise in LLMs, VLMs, Reinforcement Learning (RL), or agentic systems.
  • Hands-on experience with LLM fine-tuning, RAG, and agent frameworks.
  • Proficiency in Python and PyTorch for building and optimizing models.
  • Strong analytical skills to diagnose model bottlenecks and improve pipelines.
  • Clear communication skills and a collaborative, team-first attitude.

Nice to have

  • Publications in top AI/ML conferences such as NeurIPS, ICML, ICLR, CVPR, ACL, or EMNLP.
  • Experience with large-scale distributed training or LLM post-training pipelines.
  • Contributions to open-source agent frameworks or benchmark releases.

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