This position is in machine learning and artificial intelligence. Key responsibilities include, but are not limited to:
Responsible for the theoretical research and algorithm and model development of machine learning (especially in the field of deep learning), including but not limited to: neural network model design, meta-learning, automatic hyperparameter optimization, online learning and various optimization methods. The distributed version of the model is developed to achieve acceleration, enrich the public parallel algorithm library within the company, explore and study cutting-edge problems such as machine learning, especially deep learning, meta-learning, and provide comprehensive technical solutions based on future actual application scenarios. Provide model support for computer vision, speech recognition, natural language processing, etc., carry out innovative research and landing product development.
1.Computer, applied mathematics, statistics, pattern recognition, artificial intelligence, automation control, operations research, biology, physics / quantum computing, neuroscience, etc., master's degree or above;
2. Proficient in at least one programming language such as C / C ++, Java, Python, etc., have strong hands-on ability. Understand one or more of the current common machine learning or deep learning frameworks: Tensorflow, Pytorch, Caffe, Spark, XGBoost, etc .; 3. Have relevant open source project contribution experience, or have a winning experience in a programming or modeling contest or Familiar with common machine learning model algorithms, such as LR, GBDT, FM, Random Forest, etc .; familiar with deep learning common model algorithms, such as CNN / DNN / RNN / LSTM, etc., have complete business online DL modeling and tuning experience or field Publishing experience of top conference papers (NIPS / ICML / CVPR / KDD, etc.);
4. Familiar with common distributed programming languages and computer architectures; familiar with parallel computing / high-performance computing frameworks such as MPI / OpenMP / CUDA, and better understanding of large-scale machine learning related technologies, such as BSP / SSP / A-SGD or Data / Common machine learning optimization algorithms or mechanisms such as Model Parallelism. Have data modeling business experience or publishing experience in top conference papers (SOSP / OSDI / NSDI / EuroSys, etc.).
5. Have good logical thinking ability and data sensitivity, can read and write English papers proficiently, and have excellent scientific and technological research capabilities;