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Meta Research Scientist, LLM, GenAI (PhD) in Paris, France

Summary:

Meta is seeking an early-career research scientist to join our Llama Research team at GenAI, an organization focused on making research breakthroughs in AI. Individuals in this role are expected to be knowledgeable in research areas such as Large Language Models, Reinforcement Learning, generative models, open-ended learning. Research scientists are also expected to have a track record in helping produce new science that advances our understanding of intelligence. The ideal candidate for this position will have particular experience in finetuning language models and knowledge of offline and online reinforcement learning methods.

Required Skills:

Research Scientist, LLM, GenAI (PhD) Responsibilities:

  1. Contribute to ambitious research to advance the science of intelligence in the brain and in machines

  2. Drive state-of-the-art research with the team of researchers and engineers

  3. Collaborate effectively within their team to help advance its research goals

  4. Influence progress of relevant research communities by contributing to publications

  5. Contribute research that can be applied to Meta product development

Minimum Qualifications:

Minimum Qualifications:

  1. Currently has or is in the process of obtaining a PhD in the field of DEGREE AREA, a related field, or equivalent practical experience. Degree must be completed prior to joining Meta

  2. Expertise in deep learning, language modelling, reinforcement learning

  3. Public speaking, internal communication of complex research

  4. Familiarity with one or more deep learning frameworks (e.g. PyTorch or Jax)

  5. Programming skills (Python, pytorch)

  6. Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment.

Preferred Qualifications:

Preferred Qualifications:

  1. Experience in open-source development

  2. Experience in reinforcement learning

  3. Experience in Large Language Modeling

  4. Experience in Building Agents

  5. Experience solving complex problems and comparing alternative solutions, tradeoffs, and diverse points of view to determine a path forward.

  6. Experience working and communicating cross functionally in a team environment.

  7. Established track record of contributing to influential research, e.g. as evidenced by high-impact publications at peer-reviewed AI conferences (e.g. NeurIPS, ICML, EMNLP, ICLR, CVPR, ICCV, ACL, Interspeech and ICASSP) and/or Machine Learning journals

Industry: Internet

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