AI Researcher

Key Skills

Python Programming, Scala Programming, C++, Java Programming, Machine learning techniques, Data science techniques, SQL, Apache Hadoop, MapReduce, TensorFlow, PyTorch

Job Description

Position Overview

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As an AI Research and Development engineer, you will work on exciting projects that develop AI technologies to solve problems in various real-world applications. Your talent in conducting innovative research and development will certainly be fulfilled in your daily work. If you love challenges as a R&D engineer, this position will keep your passion ongoing. You will certainly find out so much of what you can positively impact the world via this position and meanwhile so much of what you will learn every day from the job.

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Responsibilities:

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• Collect and analyze AI requirements from customers? and/or potential applications.
• Conduct research of relevant/emerging AI technologies (e.g., deep learning frameworks) in the area of computer vision (CV) and propose the best of breeds solutions to meet the specific AI requirements.
• Tune your CV algorithms to the optimum performance to handle real-time processing requirements in production system.
• Develop proof of concepts to assess proposed AI solutions for their applicability.
• Publish relevant AI research papers when necessary and approved, and attend conferences for increasing public awareness of Huawei’s products.
• Implement AI solutions for commercialization and/or integration.
• Team with other department (e.g., hardware, big data) and provide specific feedbacks to them for improvement.
• Assist the team lead on planning of projects and definition of technology/products development road map.

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Qualifications

• Master/PhD in Computer Science, Software Engineering, Math/Statistics, focusing on AI & Machine Learning/Deep Learning.
• Working experience in computer vision/image processing/video processing.
• Hands-on skills in programming in Tensorflow/Theano/Keras/Caffe/Caffe2/PyTorch/MXNet.
• Hands-on skills in C++/Python programming.
• Good documentation skills in writing internal reports and/or publishing research papers.
• 1+ year experience in optimizing performance of deep learning models is a preferred asset.
• Solid knowledge of AI software and hardware systems, and AI workload analysis methodologies and practices is a preferred asset.