The field of industrial AI requires a variety of talent positions, covering all aspects from research and development to application, from technology to management. Here are some of the key jobs:
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1. **AI Algorithm Engineer ** : Responsible for the development and optimization of artificial intelligence algorithms, need to have a solid mathematical foundation and programming ability.
2. ** Data Scientist ** : Focus on data analysis and model building, using big data technology to extract valuable information.
3. ** Machine Learning Engineer ** : Using machine learning methods to solve real-world problems often requires a deep understanding of statistics and data analysis.
4. ** Natural Language Processing Engineer ** : An engineer who focuses on making machines understand and respond to human language.
5. ** Computer Vision Engineer ** : Handle image recognition, image analysis and other related tasks, so that the machine can \"see\" and understand the image content.
6. **AI Product Manager ** : Combining AI technology and product management knowledge, responsible for the planning and design of artificial intelligence products.
7. **AI Project Manager ** : Manage the progress, cost and team of AI projects to ensure the achievement of project objectives.
8. **AI Researcher ** : Conduct basic or applied research on artificial intelligence in academic research institutions or corporate research departments.
9. ** iot Architect\/Engineer ** : Design and implement iot solutions, including sensor integration, data transmission and processing.
10. ** Smart Chip Architecture Design Engineer ** : Focuses on designing and developing chips and hardware for AI applications.
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In addition to the technical positions mentioned above, there is also a need for business talent with business insight and industry experience, as well as HR experts and headhunters with in-depth knowledge of the AI field. With the continuous development of AI technology and the expansion of the scope of application, there will be more new, deep and creative talent needs in the future.
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To sum up, in preparing for these positions, potential job seekers can upgrade their skills and knowledge by attending relevant training courses and certification exams. For example, Google's TensorFlow Developer Certificate, Microsoft's Certified: Certifications such as Azure AI Engineer Associate and Amazon's AWS Certified Machine Learning-Specialty are recognized qualifications in the industry. At the same time, understanding the research areas and job requirements of different companies, such as Google's positions in search engines, natural language processing, computer vision and other fields, also helps job seekers to more accurately locate their development direction.