基本信息
所属部门IAIC
学历要求博士
专业名称工业人工智能
招聘人数20
职位类别未填写
专业类别物理学类
单位地址（工作地点）广东省深圳市南山区 深圳湾科技生态园11栋A座13楼（广东/深圳/不限）
职位描述/研究方向
职责要求
1、包含但不限于计算机、信息工程、人工智能、自动化、软件工程、机械工程、能源、电力、电子工程、统计学、应用数学、物理学、力学、信号处理等专业的硕、博士
2、熟悉常用机器学习算法和深度学习（CNN/RNN/GNN/注意力机制/工业视觉）等相关领域，对模式识别，概率统计、运筹学等算法原理及应用中的一项或多项有扎实的基础，对AI技术如何应用解决现实问题具备浓厚的兴趣
3、熟练掌握C/C++、Java、Go、Python等至少一门编程语言，有较强动手能力，具备良好的编程习惯。熟练掌握常见机器学习或者深度学习框架中的一个或者多个：Sklearn、PaddlePaddle、Pytorch、Tensorflow等
具备以下一项或多项的优先考虑：
-具有交叉学科背景或具备人工智能技术在泛工业领域应用相关项目经验
-熟悉模型量化、模型部署等算法工程化内容, K8s/Docker/服务网格ISTIO/NEO4J(图数据库)
Requirements:
1. Degree: Master, Doctor.
Major: Including, but not limited to Computer, information engineering, artificial intelligence, automation, software engineering, mechanical engineering, energy, electric power, electronic engineering, statistics, applied mathematics, physics, mechanics and signal processing.
2. Familiar with common machine learning algorithms and deep learning (CNN / RNN / GNN / Attention mechanism / industrial vision) and other related fields, have a solid foundation for one or more of the algorithm principles and applications such as pattern recognition, probability statistics and operations research, and have a interest in how to apply AI technology to solve practical problems
3. Master at least one programming language such as C / C + +, Java, Go and Python, have strong Practical ability and good programming habits. Master one or more common machine learning or deep learning frameworks: Sklearn、PaddlePaddle、Pytorch、Tensorflow, etc.
Priority:
-Have interdisciplinary background or project experience in the application of artificial intelligence technology in Pan industrial field
-Familiar with algorithm engineering of model quantization, model deployment, or K8s/Docker / service grid ISTIO / NEO4J (figure database)
Location: Global
1、包含但不限于计算机、信息工程、人工智能、自动化、软件工程、机械工程、能源、电力、电子工程、统计学、应用数学、物理学、力学、信号处理等专业的硕、博士
2、熟悉常用机器学习算法和深度学习（CNN/RNN/GNN/注意力机制/工业视觉）等相关领域，对模式识别，概率统计、运筹学等算法原理及应用中的一项或多项有扎实的基础，对AI技术如何应用解决现实问题具备浓厚的兴趣
3、熟练掌握C/C++、Java、Go、Python等至少一门编程语言，有较强动手能力，具备良好的编程习惯。熟练掌握常见机器学习或者深度学习框架中的一个或者多个：Sklearn、PaddlePaddle、Pytorch、Tensorflow等
具备以下一项或多项的优先考虑：
-具有交叉学科背景或具备人工智能技术在泛工业领域应用相关项目经验
-熟悉模型量化、模型部署等算法工程化内容, K8s/Docker/服务网格ISTIO/NEO4J(图数据库)
Requirements:
1. Degree: Master, Doctor.
Major: Including, but not limited to Computer, information engineering, artificial intelligence, automation, software engineering, mechanical engineering, energy, electric power, electronic engineering, statistics, applied mathematics, physics, mechanics and signal processing.
2. Familiar with common machine learning algorithms and deep learning (CNN / RNN / GNN / Attention mechanism / industrial vision) and other related fields, have a solid foundation for one or more of the algorithm principles and applications such as pattern recognition, probability statistics and operations research, and have a interest in how to apply AI technology to solve practical problems
3. Master at least one programming language such as C / C + +, Java, Go and Python, have strong Practical ability and good programming habits. Master one or more common machine learning or deep learning frameworks: Sklearn、PaddlePaddle、Pytorch、Tensorflow, etc.
Priority:
-Have interdisciplinary background or project experience in the application of artificial intelligence technology in Pan industrial field
-Familiar with algorithm engineering of model quantization, model deployment, or K8s/Docker / service grid ISTIO / NEO4J (figure database)
Location: Global
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其他要求
【薪酬福利简介】
- 薪资面议，重点关键技术，薪资open可谈
- 其他福利：五险一金+法定节假日+探亲+项目补贴+电脑补贴+其他
- 激励：资质认证激励+优秀员工激励+俩次调职级福利（入职满一年）
- 薪资面议，重点关键技术，薪资open可谈
- 其他福利：五险一金+法定节假日+探亲+项目补贴+电脑补贴+其他
- 激励：资质认证激励+优秀员工激励+俩次调职级福利（入职满一年）
