Research Scientist ML Training Infra

3 weeks ago

Dubai, United Arab Emirates Meta Full time

Meta is seeking a Research Scientist to joinour Ads Training Performance Team within the Monetizationorganization, a group focused on making a significant impact in AIby building next generation ML infra. We are responsible for theinfrastructure that trains models that power the ranking andrecommendation system for ads served in Meta. The ideal candidatewill have a keen interest in producing new ML Infra solutions toimprove model training including training performance through GPUoptimizations.

Research Scientist, ML TrainingInfra Responsibilities:

  • Develop highly scalable andperformant ML Infra.
  • Collaborate with ResearchScientists on novel research in modeling and complexsystems.
  • Apply knowledge of relevant researchdomains and coding skills to platform and framework developmentprojects.
  • Mentor other team members. Arbitratein cases of technical disagreement among team members. Play asignificant role to have a healthy cross-functionalcollaboration.

MinimumQualifications:

  • Currentlyhas, or is in the process of obtaining a Bachelor's degreein Computer Science, Computer Engineering, relevant technicalfield, or equivalent practical experience. Degree must be completedprior to joining Meta.
  • Currently has or is inthe process of obtaining a PhD in the field of Machine Learning,Artificial Intelligence, Computer Science, Information orMultimedia Retrieval, Reinforcement Learning, Mathematics, orrelated technical field, or equivalent practical experience. Degreemust be completed prior to joiningMeta.
  • Experience with research and buildinginfra for Machine Learning.
  • Experience withPython, C++, Java, or other relatedlanguages.
  • Must obtain work authorization inthe country of employment at the time of hire and maintain ongoingwork authorization during employment.

Preferred Qualifications:

  • Experience solving analyticalproblems using quantitativeapproaches.
  • Experience manipulating andanalyzing complex, high-volume, high-dimensionality data fromvarying sources.
  • Experience with developingMachine Learning Infra at scale from inception to businessimpact.
  • Proven track record of achievingsignificant results as demonstrated by grants, fellowships,patents, as well as publications at leading workshops, journals orconferences such as (e.g., NeurIPS, CVPR, ICML, ICLR, ICCV, andACL) or similar.
  • Demonstrated research andsoftware engineering experience via an internship, work experience,coding competitions, or widely used contributions in open-sourcerepositories (e.g. GitHub).
  • Experience solvingcomplex problems and comparing alternative solutions, tradeoffs,and diverse points of view to determine a pathforward.
  • Experience working and communicatingcross functionally in a teamenvironment.

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