The focus of AI engineer is to explore the trend of market development, combine Siemens products, design and deliver market expected AI solutions and related value propositions, and cooperate with business departments to show the unique role Siemens can play.
Deep learning is the development direction of advanced artificial intelligence technology.
Combined with Siemens products, explore and mine AI related technologies to solve practical problems.
Build deep learning platform selection, framework construction, related algorithm development and optimization.
Master's degree or above, major in computer, machine learning, pattern recognition, mathematics, etc.
Proficient in common machine learning algorithm related knowledge, deep learning knowledge and algorithms, algorithm research or development experience in this field.
Familiar with big data knowledge, including file storage, big data architecture, data processing, etc.
4） 具有较好的编程能力，至少熟悉一种主流编程语言 如Python, C++, Java等。
Good programming ability, familiar with at least one mainstream programming language, such as python, C + +, Java, etc.
Experience in predictive maintenance algorithm development is preferred.
Good ability to read and write English documents and technical documents.
Strong self-study ability, analytical ability and problem-solving ability, good communication, coordination and organization ability
At Siemens, we value diversity as the inclusion of and collaboration of different thinking, background, experience, expertise and individual qualities across all organization levels and dimensions. We encourage and support our employees to develop their personal skills and strengths, regardless of gender identity, nationality, age, religious beliefs etc.. We believe diversity strengthens our innovative capacity, unleashes the potential of Siemens’ employees and thereby directly contributes to our business success.
Organization: Smart Infrastructure
Company: Siemens Electrical Apparatus Ltd., Suzhou
Experience Level: Student (Not Yet Graduated)
Job Type: Part-time