Artificial Intelligence or Big Data Engineer

Artificial Intelligence or Big Data Engineer Job Description

Responsibilities:

KTI now constructs an innovative and tackled R&D team in Las Vegas, which will focus on the applications of artificial intelligence and big data technology in the industries in which the company operates (such as facial recognition, object recognition, ad. design, data acquisition, analysis, use, etc.). The team will support multiple R&D centers. You will be part of the team.

To study core algorithms in deep learning (including various neural network structures and applications) or in all fields of computer vision (target detection and recognition, especially face recognition, etc.)

Engaged in research and analysis of cutting‑edge algorithms in the field of artificial intelligence, explored the innovative application of artificial intelligence in the field of video surveillance, and worked with the product development team to optimize algorithm practicability and gain competitive advantages in practical applications;

Base on the market demand, develop the core technologies and road map of artificial intelligence or big data applications including algorithms;

Improve core technology competitiveness through innovation;

Hands on, to achieve these core technologies;

Use these core technologies to support the product development of R&D centers

At least 5 years working experience in the research and development of artificial intelligence or big data application, with profound and solid technical foundation and performance record;

Proficiency in one or more programming languages, including but not limited to Java, C, C++, Python, Shell, R, Scala, Matlab, Lua, etc. Familiar with common machine learning and computer vision open source libraries;

Have a solid foundation in mathematics and machine learning algorithms, familiar with decision tree, clustering, time series, classification tree, Boosting, SVM, random forest, collaborative filtering, regression, Bayesian networks, stochastic processes, Markov chain and other related Traditional machine learning algorithms;

Familiar with neural network theory, at least able to use Caffe, Tensor Flow, Keras, MxNet, Torch, Theano any one of the framework for modeling and training;

Familiar with CNN, RNN, LSTM, Reinforced Learning and other principles to optimize the latest model in the industry;

Smart, dedicated and innovative. Quick learner of new technologies. Leader of core technologies;

Strong communication and coordination skills;

Electronic security industry experience is preferred.

Relevant dissertation is preferred in the top academic conference journals such as CVPR, ICCV, ECCV, NIPS, ICLR, TPAMI, etc.,

Master's degree or above in Computer Science, Software Engineering, or equivalent from a top university.