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🚀 Internship

Research Scientist Intern, PhD, PyTorch Model Optimization

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Meta

19d ago

🚀 Off-cycle Internship

San Francisco

⌛ Closed

AI generated summary

  • The candidate must have a PhD in Computer Science or related field, experience in machine learning/deep learning domains, knowledge of ML systems, work authorization, familiarity with PyTorch/TensorFlow/JAX, experience with distributed GPU clusters, publications in top ML/System conferences, and intent to return to their degree program after the internship.
  • The Research Scientist Intern at Meta will be responsible for utilizing AI and machine learning techniques to advance machine learning frameworks, collaborating with users to enable new use cases for PyTorch, and developing innovative optimization algorithms for fine-tuning or inference of AI models.
Applications are closed

Off-cycle Internship

Research & Development, Software EngineeringSan Francisco

Description

  • Meta is seeking a Research Scientist Intern to join our Meta PyTorch Model Optimization Team. Our team’s mission is to make PyTorch faster and easier to use in order to create and maintain a state-of-the-art machine learning framework that is used across Meta and the entire industry.
  • In this role you will get to work on various model optimization techniques like quantization and sparsity to push the boundaries of state of the art performance of running popular AI models.

Requirements

  • Currently has, or is in the process of obtaining, PhD degree in the field of Computer Science or a related STEM field
  • Experience in one or more of the following machine learning/deep learning domains: Running fine-tuning and inference/evaluation on AI models, ML theory: Basic knowledge about ML models in different modalities like LLM (Large Language Models), Vision (VITS, MVITS) and Multimodal and how scale impacts performance, ML systems: AI infrastructure, machine learning accelerators, high performance computing, machine learning compilers, GPU architecture, machine learning frameworks, distributed systems, on-device optimization.
  • Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment
  • Preferred Qualifications:
  • Experience or knowledge on training models at scale using PyTorch/TensorFlow/JAX.
  • Experience or knowledge on working with a distributed GPU cluster.
  • Publications in top tier ML or System Conferences such as ASPLOS, ICML, ICLR, KDD, NeurIPS, MLSys, SOSP, OSDI, NSDI.
  • Intent to return to degree-program after the completion of the internship/co-op

Education requirements

Currently Studying
PhD

Area of Responsibilities

Research & Development
Software Engineering

Responsibilities

  • Apply relevant AI and machine learning techniques to advance the state-of-the-art in machine learning frameworks.
  • Collaborate with users of PyTorch to enable new use cases for the framework both inside and outside Meta.
  • Develop novel, accurate optimization algorithms for AI models during fine-tuning or inference.

Details

Work type

Full time

Work mode

office

Location

San Francisco