обновлено 5 дней назад
Research Scientist (Generative & Agentic AI)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Research Scientist (Generative & Agentic AI) (LLMs/VLMs/AI agents): Building generative and agentic AI systems that reason, plan, use tools, and solve real-world problems with an accent on post-training, multimodal intelligence, and foundation model performance. Focus on designing model and agent evaluations, improving training and inference efficiency, and translating frontier research into production applications.
Location: Taipei, Taiwan
Company
is a SaaS company that uses artificial intelligence to support business decision-making and develop intelligent software products.
What you will do
- Research and build agentic AI systems with reasoning, planning, tool use, memory, and multi-agent collaboration.
- Advance post-training methods such as SFT, RLHF, RL with verifiable rewards, and preference optimization.
- Improve the performance, efficiency, and scalability of foundation models across training, inference, and test-time computation.
- Design rigorous evaluations and benchmarks for models and agents in real-world scenarios.
- Collaborate with scientists and engineers to bring research into production applications.
- Track frontier research, define new research directions, and publish findings at leading AI and machine learning conferences.
Requirements
- Master’s degree or Ph.D. in Computer Science, Electrical Engineering, Mathematics, or a related field, with research experience in AI or machine learning.
- Deep understanding of foundation models and expertise in at least one area: LLMs, VLMs or multimodal models, reinforcement learning, or agentic systems.
- Hands-on experience with LLM fine-tuning, RAG, agent frameworks, tool use, function calling, or product prototyping.
- Proficiency in Python and PyTorch, with the ability to build, train, and optimize models.
- Ability to analyze model behavior, diagnose bottlenecks, and improve training and inference pipelines.
- Clear communication skills and a collaborative, team-first approach.
Nice to have
- Publications at top AI and machine learning 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, models, or benchmarks.
- Experience using AI-assisted coding workflows.
Culture & Benefits
- Collaborative work across research and engineering teams.
- Opportunity to connect frontier AI research with real-world product impact.
- Work in a fast-paced environment focused on generative and agentic AI.
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