엔비디아(NVIDIA)

AI Research Scientist

4년 이상서울상시 채용

경력: 4년 이상
고용 형태: 정규직
마감: 상시 채용
지역: 서울서울특별시 영등포구 당산로41길 11 (당산동5가, 당산SK V1 center W1209호)
직군·직무: 개발데이터 사이언티스트, 소프트웨어 엔지니어
출처: 원티드

이 공고에서 요구하는 AI 역량

AI 활용 필수

AI 관련 항목

주요 업무3곳
자격 요건3곳
우대 사항2곳

공고에서 찾은 문장

주요 업무
Conduct cutting-edge research in agentic AI, including reasoning, planning, tool use, and autonomous problem-solving.
주요 업무
Advance the capabilities and efficiency of foundation models and agentic systems through innovative training and inference-time methods.
주요 업무
Develop advanced Korean-language AI models and agentic systems, establishing methods and training recipes that generalize to other languages and regions.
자격 요건
Strong expertise in one or more of the following areas: LLMs, agentic AI, reasoning, RL, efficient model training, synthetic data generation, data-efficient learning, RL, distillation, or self-improving AI.
자격 요건
Strong understanding of modern deep learning methods and foundation models.
자격 요건
Excellent programming skills in Python and experience with deep learning frameworks such as PyTorch.
우대 사항
Research contributions to state-of-the-art agentic systems, reasoning models, or autonomous AI.
우대 사항
Significant open-source contributions to foundation models, datasets, or agentic AI frameworks.

요구 경력

4년 이상

회사 소개

NVIDIA is searching for outstanding AI researchers to join the NVIDIA Research Korea team. Our mission is to advance the frontiers of agentic AI by developing more capable, efficient, and self-improving AI systems. We focus on fundamental research in agentic reasoning, synthetic data generation, data-efficient learning, scalable training, and iterative self-improvement, exploring how AI systems can continuously improve their capabilities while reducing their dependence on expensive human supervision and computational resources.

주요 업무

• Conduct cutting-edge research in agentic AI, including reasoning, planning, tool use, and autonomous problem-solving. • Develop novel methods for data-efficient learning, synthetic data generation, data selection, and scalable model training. • Explore self-improvement techniques, including RL, distillation, self-training, and learning from model-generated feedback. • Advance the capabilities and efficiency of foundation models and agentic systems through innovative training and inference-time methods. • Develop advanced Korean-language AI models and agentic systems, establishing methods and training recipes that generalize to other languages and regions. • Publish original research at leading conferences and contribute to open-source research. • Collaborate with researchers across NVIDIA and external academic institutions. • Mentor research interns from NVIDIA-KAIST Joint AI Research Lab and contribute to a collaborative research environment with KAIST. • Present research findings at conferences, workshops, and other scientific events. • Transfer research innovations to NVIDIA product teams.

자격 요건

• PhD in AI, Computer Science, Electrical Engineering, or a related field (or equivalent experience). • At least 4 years of relevant research experience. • Strong expertise in one or more of the following areas: LLMs, agentic AI, reasoning, RL, efficient model training, synthetic data generation, data-efficient learning, RL, distillation, or self-improving AI. • Publications at leading conferences such as NeurIPS, ICML, ICLR, COLM, ACL, EMNLP, or CVPR. • Strong understanding of modern deep learning methods and foundation models. • Excellent programming skills in Python and experience with deep learning frameworks such as PyTorch. • Ability to identify important research problems, develop novel approaches, and conduct rigorous empirical evaluations. • Excellent communication skills and ability to collaborate effectively across research teams.

우대 사항

• Research contributions to state-of-the-art agentic systems, reasoning models, or autonomous AI. • Experience with large-scale distributed training, efficient post-training, or inference-time scaling. • Impactful contributions to Korean-language AI, multilingual foundation models, or cross-lingual transfer. • Significant open-source contributions to foundation models, datasets, or agentic AI frameworks.

혜택 및 복지

자세한 사항은 홈페이지 참고

회사 정보

엔비디아(NVIDIA)홈페이지

복지

인공지능

서울특별시 영등포구 당산로41길 11 (당산동5가, 당산SK V1 center W1209호)지도 보기