
Research Scientist (Generative AI)
- Taipei City
- Permanent
- Full-time
- Design and implement novel algorithms and architectures for LLMs, VLMs, and RL with both research and product impact.
- Conduct experiments to improve the performance, efficiency, and scalability of generative models across language and vision tasks.
- Analyze experimental results, contribute to internal knowledge, and optionally publish key findings in leading AI/ML conferences.
- Collaborate with cross-functional teams to integrate models into real-world applications.
- Continuously review recent publications and preprints in the field, and evaluate their relevance to Appier's product roadmap.
- Drive innovation within the team by proposing and exploring new research directions and ideas.
- Master's degree or Ph.D. in Computer Science, Electrical Engineering, Mathematics, or a related field, with research experience in AI, ML, or related technical areas.
- Solid understanding of modern AI models and algorithms, with expertise in at least one of the following: LLMs, computer vision (CV), multimodal models (VLMs), or RL.
- Candidates should have experience utilizing LLMs for research or product prototyping. Familiarity with AI-assisted coding tools (e.g., Vibe coding) is a plus.
- Proficient coding skills in Python and hands-on experience with machine learning frameworks like PyTorch. Able to build and optimize models effectively.
- Strong ability to analyze model behavior, diagnose bottlenecks, and improve training pipelines.
- Clear communication skills and a team-first attitude. Able to explain technical ideas to both technical and non-technical teammates, and enjoy working in a fast-paced, collaborative environment.
- Experience in academic research, with publications in top AI/ML conferences or journals (e.g., NeurIPS, ICML, ICLR, CVPR, ACL).
- Proven ability to work well in teams and drive research projects from idea to implementation.
- Contributions to open-source projects or involvement in research communities.
- Passion for pushing the frontier of generative AI and bridging research with impactful real-world applications.