Apple

Deep Learning Specialist

  • Experience 0-5 Years
  • Category Engineering
  • Location Santa Clara, CA

Job Description

The video engineering group is looking for a deep learning specialist with a strong emphasis applying modern neural networks to sensor data including image and video analysis. In this position, you will work together with similar minds in a unique development team where your skills and expertise will be applied to Apple products.

Responsibilities

The deep learning specialist will work in a small and dynamic team to design and implement state of the art neural network algorithms for Apple products, including detection and classification techniques spanning a range of sensor modalities.

Qualifications

  • Understanding of state of the art deep learning techniques
  • Strong understanding of CNNs, recurrent nets, supervised and unsupervised learning, and optimization techniques
  • Experience working with one or more deep learning frameworks such as Caffe, Theano, Torch, TensorFlow, MXNet
  • Strong desire and drive to build robust and efficient solution in consumer products using deep learning technology
  • Solid Python and C/C++ development skills
  • Team player
  • Self motivated
  • Excellent problem solving skills
  • Excellent communication skills
  • Can work under stress and uncertainty
  • Fast learner

Education

PhD in Machine Learning, Deep Learning, Computer Vision or similar Alternatively, a comparable industry career, with significant experience in state-of-the-art Deep Learning, Computer Vision, Machine Learning and Pattern Recognition fields

Additional Requirements

Experience/knowledge of large scale machine learning applied to very large and diverse datasets (preferred) Solid fundamental computer vision methods and concepts (preferred) Experience shipping products, especially ones incorporating machine learning (preferred) Experience/knowledge of GPU computing/CUDA kernels (preferred) Experience/knowledge of software development on embedded platforms (preferred)

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