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💼 Job

Research Scientist, Systems for ML (PhD)

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Meta

11d ago

💼 Graduate Job

New York +1

AI generated summary

  • Bachelor's and Ph.D. degrees in Computer Science or Computer Engineering, proficiency in Python and C++, experience in systems and machine learning, proficiency in PyTorch, and experience with leading conferences and publications.
  • The research scientist will conduct cutting-edge research in machine learning systems, focusing on learning data semantics and developing innovative AI system designs. They will collaborate with researchers and partners, publish results, and contribute to Meta's product development.

Graduate Job

DataNew York, Boston

Description

  • Meta is seeking Research Scientists to join Fundamental AI Research (FAIR). We are committed to advancing the field of artificial intelligence by making fundamental advances in technologies to help interact with and understand our world. We are seeking individuals passionate in solving systems challenges in areas such as deep learning, computer vision, audio and speech processing, natural language processing. Our researchers have opportunities to make core algorithmic advances and apply their ideas at an unprecedented scale.
  • The mission of Meta FAIR's SysML research is to explore and advance systems to unlock the potential of AI technologies. We aim to sustainably accelerate machine learning innovations with novel system solutions and advance AI infrastructures at scale.

Requirements

  • Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta.
  • Currently has or is in the process of obtaining a Ph.D. degree in Computer Science or Computer Engineering with a focus in Systems and Machine Learning or relevant technical fields. Degree must be completed prior to joining Meta.
  • Experience with Python, C++, C, Lua or other related languages and with PyTorch framework.
  • Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment.
  • Preferred Qualifications:
  • Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as NeurIPS, ICML, ICLR, MLSys, ISCA, ASPLOS, CGO, PLDI, PACT, HPCA, MICRO, or similar.
  • Experience developing and optimizing systems for at-scale machine learning execution.
  • Experience in real-system implementations.
  • Experience devising data-driven models and real-system experiments and design implementation for AI system optimization.
  • Experience with scalable machine learning systems, resource-efficient AI data and algorithm scaling, or neural network architectures.
  • Experience with memory and energy-efficient AI systems, environmentally-sustainable AI system designs, or AI-driven system optimization.
  • Experience solving analytical problems using quantitative approaches.
  • Experience in utilizing theoretical and empirical research to solve problems.
  • Experience working and communicating cross functionally in a team environment.

Education requirements

Currently Studying
Bachelors

Area of Responsibilities

Data

Responsibilities

  • Perform state of the art research to advance the science and technology of machine learning systems.
  • Perform research that enables learning the semantics of data (images, video, text, audio, and other modalities).
  • Devise better data-driven models of AI system design and optimization.
  • Contribute research that leads to innovations in: scalable machine learning systems, resource-efficient AI data and algorithm scaling and neural network architectures, memory and energy-efficient AI systems, environmentally-sustainable AI system and hardware designs.
  • Collaborate with researchers and cross-functional partners including communicating research plans, progress, and results.
  • Publish research results and contribute to research that impacts Meta product development.

Details

Work type

Full time

Work mode

office

Location

New York, Boston