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Laplacian RoboticsEngineering

Cross-Embodiment Learning Engineer

Seongnam-sionsitemid

Posted 2mo ago · via Workable

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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.…

Read the full description on Laplacian Robotics's site →

What we'd score you on

reqspace match rubric

Five dimensions, recruiter-grade. Upload your resume and we'll generate a written explanation of where you fit and where the gaps are.

1

Skills match

For this role: python, pytorch, claude, linear, notion…

2

Level fit

This role is mid-level. We check your trajectory against it.

3

Domain experience

Your work in the role's domain matters more than your years total. We weight recent and direct experience.

4

Recency

A skill you used last quarter weighs more than one from five years ago. We grade on recency, not lifetime.

5

Location fit

This role is based in Seongnam-si. We weight your proximity and willingness to relocate.

Score yourself on this role.
Free · no card · written explanation included
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Skills in this role

Pulled from the job description. These are the keywords we'll weight when scoring your fit.

pythonpytorchclaudelinearnotionslackworkable

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