Staff. Engineer - Deep Learning and Hardware acceleration

Company: La Haus
Location: Palo Alto, California, United States
Type: Full-time
Posted: 30.MAY.2021
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Summary

Key Responsibilities * Work in a collaborative environment to develop cutting-edge deep learning algorithms and software. * Engage in cutti...

Description

Key Responsibilities

  • Work in a collaborative environment to develop cutting-edge deep learning algorithms and software.
  • Engage in cutting-edge research in computer vision and deep learning to solve real-world problems for mobile use cases.
  • Ideate, prototype, test and launch future technologies.
Minimum Qualifications

Requirements
  • Senior Engineers PhD degree in Electrical Engineering, Computer Engineering, Computer Science, with 3 to 5 years of industry experience or masters degree with additional equivalent industry experience.
  • Junior Engineers PhD degree in Electrical Engineering, Computer Engineering, Computer Science, fresh graduates to 3 years of industry experience or masters degree with additional equivalent industry experience.
  • Track record of developing demanding deep learning algorithms and applications.
  • Strong mathematical foundation in machine learning and deep learning.
  • Experience working with deep learning frameworks like Caffe, TensorFlow, Theano and MxNet.
  • Strong programming skills in C, C++, Perl, or Python.
  • Strong background in computer architecture.
  • Experience with systems-level performance modeling, profiling, and analysis.
  • Experience in characterizing and modeling of system-level performance, executing comparison studies and documenting and publishing results.
Preferred Qualifications
  • Familiarity with GPU computing (CUDA, OpenCL) and HPC (MPI, OpenMP).
  • Strong background in smartphone architecture.
  • Strong track record of Android development.
  • Hands-on experience on developing deep learning neural networks on mobile platforms.
InnoPeak Technology is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, gender, sexual orientation, gender identity or expression, religion, national origin, marital status, age, disability, veteran status, genetic information, or any other protected status.

 
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