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Open nowPosted 141 days ago

Research Scientist - Physical AI & Robot Foundation Models

LG AI Research37 open roles

Where
Gangseo-gu, Seoul, South Korea
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Your applicationOpen nowResearch Scientist - Physical AI & Robot Foundation ModelsLG AI Research · Gangseo-gu, Seoul, South Korea
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The clock on this job

Early applications get read.

13.9% of postings close within 7 days. Measured by our own scanner across the market. LG AI Research postings stay open a median of 43 days.

Share of postings closed within
  1. 2.2%1 day
  2. 4.7%3 days
  3. 13.9%7 days
  4. 22.4%14 days
  5. 38.1%30 days
  6. 59.0%60 days
This job: posted 141 days ago

LG AI Research median: 43 days open

The posting

팀 소개

Physical Intelligence Lab은 혁신적인 Robot Foundation Model(RFM)을 직접 연구·개발하며, 글로벌 최고 수준의 Physical AI 기술을 만들어가고 있습니다.

로봇이 시각 정보를 이해하고 언어 지시를 해석해 실제 환경에서 적절한 행동을 수행할 수 있도록 하는 차세대 로봇 지능 모델을 함께 만들어갈 분을 찾습니다.

이를 위해 대규모 로봇 학습 데이터 구축, 시뮬레이션 기반 학습 및 검증, 실제 로봇 환경에서의 성능 평가를 수행하며, 다양한 작업 조건과 환경 변화에 강건하게 대응할 수 있는 범용 로봇 지능의 일반화 성능 향상 연구를 수행하게 됩니다.

수행 업무

  • 신규 RFM 모델 아키텍처 및 학습 방법론 개발
  • RFM 사전학습·사후학습(SFT, RL) 성능 개선
  • 로봇 학습 데이터(Real/Sim/Web) 수집·구성 및 data mixing 전략 연구를 통한 generalization 향상
  • VLA / World Model 등 최신 연구 동향 분석 및 내부 RFM 통합·개선
  • 연구/개발 성과의 제품·서비스 적용

지원자격

  • 필수사항 - 컴퓨터 비전·머신러닝·로보틱스 등 유관 분야 석사 학위 및 관련 경력 3년 이상, 또는 박사 학위 보유자 (졸업 예정자 포함) - RFM(VLA, World Model 등) 또는 로봇 학습(Imitation Learning, Reinforcement Learning 등) 관련 연구/개발 경험 보유 - PyTorch 등 딥러닝 프레임워크를 활용한 모델 구현 및 학습 역량 보유
  • 우대사항 - 대규모 데이터셋 구축 및 데이터 전략 수립 경험 보유 - 시뮬레이션 환경(Isaac Sim, MuJoCo 등) 또는 실제 로봇 플랫폼 활용 경험 - 멀티모달 파운데이션 모델 사전학습/사후학습 경험 - Top-tier 학회(CVPR, NeurIPS, ICML, ICLR, CoRL, RSS 등) 논문 게재 실적 - 대규모 분산 학습 인프라 활용 경험

전형절차

  • 서류심사 → 코딩테스트 & LG Way Fit Test(인성검사) → 기술 인터뷰(대면) →Culture Fit 인터뷰(대면) 최종 합격

* 전형 절차는 변경될 수 있습니다. 서류 합격 시 전형 절차에 대해 별도로 안내 해 드립니다.

현재 LG AI연구원은 병역지정업체가 아님으로, 전문연구요원 채용 및 전직이 불가함을 알려드립니다.

지원시 문제가 있을 경우 [email protected] 로 문의 부탁드립니다.

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