Robot Fleet Platform Engineer
Laplacian Robotics
Cross-Embodiment Learning Engineer
Laplacian Robotics· Engineering
About this role
서로 다른 로봇·arm·gripper의 state/action을 공통 표현으로 정규화하고, UMI(Universal Manipulation Interface), ego-centric video 등 robot-free human demonstration 데이터까지 통합 활용하여, 하나의 policy와 데이터를 다양한 embodiment로 전이, 학습할 수 있는 기술을 개발하는 역할입니다. '한 번 배운 것을 모든 로봇으로 확장'하는, 스택의 확장성을 책임집니다.
In this role, you normalize the states/actions of different robots, arms, and grippers into a shared representation and integrate robot-free human demonstration data (UMI, ego-centric video, and more) so that a single policy and dataset can transfer and learn across diverse embodiments and also own the scalability of our stack-learn once, extend to every robot.
주요업무 (Key Responsibility)
- 서로 다른 embodiment(robot·arm·gripper)의 state/action을 공통 표현으로 정규화
- UMI, ego-centric video 등 robot-free human demonstration 데이터의 통합·활용
- 하나의 policy·데이터를 다양한 embodiment로 전이(transfer)하는 학습 기법 개발
- Cross-embodiment 일반화 성능을 정량 평가하는 벤치마크 설계
- Normalize states/actions across different embodiments (robots, arms, grippers) into a shared representation
- Integrate and leverage robot-free human demonstration data (UMI, ego-centric video, etc.)
- Develop learning methods that transfer a single policy/dataset across diverse embodiments
- Design benchmarks that quantify cross-embodiment generalization
- Cross-embodiment learning, transfer learning, 또는 robot manipulation 관련 3~5년의 연구·개발 경험
- Imitation learning, representation learning, 또는 multi-embodiment policy 학습 경험
- Python·PyTorch 기반 모델 학습 역량
- 다양한 로봇 형태 또는 demonstration 데이터를 다뤄본 경험
- 컴퓨터공학·AI·로봇공학 관련 석사 이상 또는 그에 준하는 경험
- 3–5 years of research/engineering experience in cross-embodiment learning, transfer learning, or robot manipulation
- Experience with imitation learning, representation learning, or multi-embodiment policy learning
- Strong model training skills in Python and PyTorch
- Experience working with diverse robot form factors or demonstration data
- Master's degree in CS, AI, Robotics, or equivalent experience
우대사항(Preferred)
- Cross-embodiment learning, UMI, ego-centric video 기반 학습 관련 연구 실적
- Representation learning 또는 domain adaptation 경험
- 다양한 robot·gripper 하드웨어를 다뤄본 경험
- 로봇공학·AI 석/박사 학위
- 대규모 heterogeneous 로봇 데이터셋 구축·활용 경험
- Research track record in cross-embodiment learning, UMI, or ego-centric video based learning
- Experience with representation learning or domain adaptation
- Experience with diverse robot/gripper hardware
- Master/PhD in Robotics or AI
- Experience building/using large heterogeneous robot datasets
- Unlimited AI token (Claude) — AI 도구 사용에 제한이 없습니다.
- Minimal meetings with fast decision-making — 불필요한 회의를 최소화하고 빠르게 의사결정합니다.
- Modern intranet/tools — Google Workspace, Slack, Notion, Linear, Workable, Flex.team 등.
Frequently Asked Questions
Is the salary disclosed for the Cross-Embodiment Learning Engineer position at Laplacian Robotics?
The salary for this Cross-Embodiment Learning Engineer role at Laplacian Robotics is not publicly listed. Click "Apply Now" to learn more about the compensation package on their official careers page.
Where is the Cross-Embodiment Learning Engineer position at Laplacian Robotics located?
This Cross-Embodiment Learning Engineer role at Laplacian Robotics is based in Seongnam-si, Gyeonggi-do, South Korea. The position is listed as on-site or hybrid. Check the full job description or apply directly to confirm the work arrangement.
Is the Cross-Embodiment Learning Engineer role at Laplacian Robotics full-time or part-time?
This is listed as a Full time position. It is posted as a Cross-Embodiment Learning Engineer role in the Engineering department at Laplacian Robotics.
Which team or department does the Cross-Embodiment Learning Engineer at Laplacian Robotics belong to?
This Cross-Embodiment Learning Engineer position is part of the Engineering department at Laplacian Robotics. See the full job description for more information about the team structure and responsibilities.
How do I apply for the Cross-Embodiment Learning Engineer position at Laplacian Robotics?
Click the "Apply Now" button on this page. You will be redirected to Laplacian Robotics's official application portal hosted on workable where you can submit your application directly.
When was the Cross-Embodiment Learning Engineer job at Laplacian Robotics posted?
This Cross-Embodiment Learning Engineer position at Laplacian Robotics was posted on Aug 21, 2026. Apply as soon as possible — early applications are often reviewed first.
Cross-Embodiment Learning Engineer
Laplacian Robotics
You'll be redirected to Laplacian Robotics's official application page on workable.