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Research Scientist, Machine Learning (PhD)

Logo of Meta


27d ago

💼 Graduate Job


AI generated summary

  • You must have a PhD in Machine Learning or related field, research experience, expertise in programming languages like Java or Python, and a proven track record of achieving results in publications or patents. Familiarity with ML Frameworks like PyTorch or Tensorflow is a plus.
  • You will develop scalable machine learning models, suggest feature improvements, collaborate with engineering, optimize methods for parallel processing, and provide feedback aligned with Meta’s Performance Philosophy.

Graduate Job

Research & Development, DataLondon


  • As a Research Scientist, you will help build machine learning systems and models behind Meta’s products, create web applications that reach millions of people, build high volume servers and be a part of a team that’s working to help connect people around the globe.


  • Minimum Qualifications:
  • Currently has, or is in the process of obtaining a PhD degree or completing a postdoctoral assignment in the field of Machine Learning, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta.
  • Research and/or work experience in machine learning, deep learning, reinforcement learning, NLP, recommendation systems, pattern recognition, signal processing, data mining, artificial intelligence, information retrieval or computer vision.
  • Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Experience in systems software or algorithms.
  • Experience in at least one of the following: Java, C/C++, Perl, PhP, or Python Demonstrated software engineer experience via an internship, work experience, coding competitions, or used contributions in open source repositories (e.g. GitHub)
  • Preferred Qualifications:
  • Proven track record of achieving results as demonstrated by grants, fellowships, patents, as well as first-authored publications at workshops or conferences such as ICML, NIPS, KDD or similar
  • Experience solving complex problems and comparing alternative solutions, tradeoffs, and diverse points of view to determine a path forward
  • Experience with Hadoop/Hbase/Pig or Mapreduce/Swazall/Bigtable
  • Experience working with ML Frameworks such as PyTorch, Spark ML or Tensorflow
  • Experience working and communicating cross functionally in a team environment

Education requirements

Currently Studying

Area of Responsibilities

Research & Development


  • Develop highly scalable classifiers and tools leveraging machine learning, regression, and rules-based models with a high degree of autonomy
  • Suggest, collect and synthesize requirements and create effective feature roadmap
  • Build strong crossfunctinal partnerships and code deliverables in tandem with the engineering team
  • Adapt standard machine learning methods to best exploit modern parallel environments (e.g. distributed clusters, multicore SMP, and GPU) Actively seek and give feedback in alignment with Meta’s Performance Philosophy


Work type

Full time

Work mode