Senior Deep Learning Algorithm Design Architect

Job description

  1. Research and development the state of art deep neural network architectures to solve a variety of computer vision and NLP applications 
  2. Software performance bottleneck analysis in CNN/RNN/LSTM architectures and design
  3. Development of AI profiling tools for neural processor engines to optimize the entire deep neural network architectures
  4. Create software optimizations to accelerate neural net operations using new designed operation nodes, such as depth-wise, hash-swish, etc.
  5. Deepen knowledge of leading edge neural network models from TensorFlow/Tlite, Kera, Caffe/Caffe2
  6. Enhance validation techniques and tools for performance, accuracy and power of neural network models


  1. M.S./PhD in Computer Science, Machine Learning, Mathematics or similar field (Ph.D. is preferred)
  2. 3+ years of industry/academia experience with deep learning algorithm development and optimization.
  3. Experience in deep networks (CNN, DBN, RNN, LSTM, DCN) or reinforcement learning (RL)
  4. Experience with classification and regression algorithms (e.g. SVM, MLP)
  5. Strong understanding of machine learning algorithms & principles, and numerical optimization
  6. 3-5 years of software engineering experience in an academic or industrial setting.
  7. Excellent Python, C++, and object-oriented programming skills demonstrated through relevant industry experience
  8. Hands-on experience in computer vision and deep learning frameworks, e.g., OpenCV,Tensorflow,Keras,Pytorch, and Caffe.
  9. Strong understanding of machine learning algorithms & principles, and numerical optimization
  10. Ability to quickly adapt to new situations, learn new technologies, and collaborate and communicate effectively.
  11. Experience with parallel computing is a plus.
  12. Top-tier conference publication records, including but not limited to CVPR, ICCV, ECCV, NIPS, ICML, is a strong plus.


10052 Mesa Ridge Court, Suite 101 San Diego, CA 92121


If interested, please send your resume to: