Paris-based Few-Shot Robotics Learning Engineer

Edison Smart®

Paris

Vor Ort

EUR 95.000 - 130.000

Vollzeit

vor 13 Stunden
Sei unter den ersten Bewerbenden

Eine vollständige Bewerbung in einer Minute

Maßgeschneiderter Lebenslauf und Anschreiben – versandbereit.

Schaffe es an den ATS-Filtern vorbei

Benefits dieser Stelle

Full relocation support to Paris
Open salary for the right candidate
English speaking team

Zusammenfassung

Edison Smart® in Paris is seeking a Robot Learning Research Engineer to design few shot imitation learning algorithms and drive production-ready research for real factory deployment.

You will explore data-efficient learning, publish findings, and help shape the long-term research agenda as one of the first hires. English-speaking team and strong collaboration with the vision and integration groups are expected.

Qualifikationen

  • PhD in robotics, machine learning or a related field from a leading research lab.
  • Strong publications in top venues and hands-on robotics research experience.
  • Hands-on experience training and debugging learning systems on real robots.

Aufgaben

  • Design, prototype and evaluate few shot imitation learning algorithms.
  • Advance state-of-the-art in imitation learning and policy learning for robots.
  • Run rigorous experiments on real robots, including humanoids and industrial arms.
  • Turn research prototypes into production-ready algorithms.
  • Collaborate with Vision & Perception and Integration teams to deploy research.

Kenntnisse

Python
Research
Experimentation
English

Ausbildung

PhD in robotics or ML

Tools

PyTorch

Jobbeschreibung

Edison Smart® in Paris is seeking a Robot Learning Research Engineer to design few shot imitation learning algorithms and drive production-ready research for real factory deployment.

You will explore data-efficient learning, publish findings, and help shape the long-term research agenda as one of the first hires. English-speaking team and strong collaboration with the vision and integration groups are expected.

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