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Research Engineer

  • CDD
  • Paris
  • Publié il y a 1 an
  • Les candidatures sont actuellement fermées.

Facebook

Meta is seeking Research Engineers to join FAIR, our world-class research lab. We are seeking individuals to work with our reinforcement learning team to build novel algorithms grounded in solid principles that can scale to efficiently solve complex real-world problems. Our research spans different aspects of reinforcement learning with particular focus on unsup/self-supervised RL to build behavioral foundation models. The candidate should have a solid background in machine learning and reinforcement learning, with experience in building and managing complex reinforcement learning pipelines at scale.

Research Engineer Responsibilities:

  • Collaborate on the development of novel behavioral foundation models that enable agents to solve a wide range of problems with little to no retraining.
  • Develop the code infrastructure needed to train and test models efficiently at scale in a variety of simulated environments.
  • Collaborate on building demos to illustrate scientific breakthroughs.

Minimum Qualifications:

  • Effective programming skills (Python, C++)
  • Currently has, or is in the process of obtaining, a Masters degree with relevant research experience in Computer Science or related fields.
  • Solid background on the foundations of machine learning and reinforcement learning.
  • Experience in working on complex machine learning code bases at scale.
  • Experience collaborating within a research team to solve complex problems.

Preferred Qualifications:

  • Lead-authored publications at peer-reviewed conferences (e.g. NeurIPS, ICLR, CVPR or similar)
  • Currently has, or is in the process of obtaining, a PhD degree in Computer Science or related fields.
  • Demonstrated machine learning experience in one of the following: internship, open-source activity, data science competitions
  • Experience in creating high-performance implementations in deep learning frameworks (such as pytorch, tensorflow)
  • Experience in using complex simulation platforms.

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