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Microsoft Senior Machine Learning Research Engineer 
United States, Washington 
433280082

13.08.2024

Strategic Planning and Architecture

This role is for a highly motivated Senior Machine Learning Research Engineer with a solid background in neural networks and hardware. You will be involved with both model development, data type analysis,

Required Qualifications

  • Doctorate or Master's in relevant field

    • OR equivalent experience.

  • Experience in ML systems/Model optimizations/Efficient model architecture.

Other Requirements

  • Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include, but are not limited to the following specialized security screenings: Microsoft Cloud Background Check:
    • This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.

Preferred/Additional Qualifications:

  • Master's Degree/PhDin Machine learning, ComputerArchitecture/Systems, High-PerformanceComputingor related areas.
  • 3+ years experience in ML systems/Model optimizations/Efficient model architecture.
  • Track recordoforiginal research anddelivering novel resultsin ML systems area.
  • Hands-on experiencewithframeworks such asPyTorch/TensorFlow/TensorRT.
  • Deep knowledge ofCNN/transformer architecture andoptimizationstrategies– quantization, sparsity, NAS, sharding,KV Cache, Flash Attention.
  • Solid programming skills in Python/C/C++.
  • Experience inimplementing low-level linear algebra/BLASkernelsand performance optimizations.
  • Outstanding communication skills.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:Microsoft will accept applications for the role until August 28, 2024.


Responsibilities
  • Driving model/HW codesign.
  • Developing andanalysingnovel NN architectures.
  • Inventing novellow-precisiondata formats.
  • Inventing novel model architectures.
  • Collaborating withdata scientists and ML researchers.
  • Interfacing with HW architecture teams.
  • Interfacing with SW framework teams.
  • Embody our