AI Research and Development Engineer

1. Meteorological AI model development and optimization

- Responsible for the design, training, fine-tuning and inference of meteorological AI models, ensuring the accuracy and efficiency of the model, and particularly focusing on improving downscaling and short-term forecasting abilities.

- Use pattern forecasting and AI technology, fuse multi-source meteorological data, continuously optimize the meteorological AI model, and improve forecast accuracy and timeliness.

- Participate in the development, practice and deployment of meteorological large models, and promote the efficient application of models in actual business.

2. Data processing and analysis

- Process, analyze, store and apply various meteorological data, including satellite, radar, ground observation data, etc., mine the potential value of the data, and provide data support for meteorological AI models.

3. Algorithm development and innovation

- Research and development of AI algorithms suitable for the meteorological field, combined with pattern forecast methods, explore new forecast technologies and means, and improve the effects of downscaling forecast and short-term forecast.

- Track international cutting-edge technology dynamics, actively participate in technological innovation and scientific research projects, and promote the application and development of meteorological AI model technology in the field of meteorological forecasting.

4. System development and integration

- Assist in the development of meteorological service systems, combine meteorological AI models with actual application scenarios, integrate and test the system, and ensure its stability and reliability.

- Participate in the construction and optimization of meteorological forecasting platforms, providing efficient and convenient meteorological services to meteorological departments and related industries.

5. Technical exchange and cooperation

- Have good team spirit and communication skills, be able to work closely with team members to complete project tasks.

- Actively participate in domestic and international academic exchange activities, share research results with peers, and enhance the company's influence in the meteorological field.

Four. Job Requirements

1. Professional background

- Applicants with meteorological background, and those with rich experience in short-term weather forecasting and downscaling are preferred, and those with doctoral degrees are preferred.

- Candidates with experience in meteorological large-scale model development, implementation, and deployment are preferred.

- "Participate in national meteorological projects" or "Collaborate with international meteorological agencies" experience is preferred.

2. Technical skills

- Familiar with the principles of meteorological AI models, with rich practical experience, those with meteorological AI model development project experience are preferred.

- Proficient in using Python for algorithm development, familiar with PyTorch, TensorFlow, etc. Deep learning frameworks, able to independently complete the implementation and optimization of complex algorithms.

- Familiar with meteorological industry data system, familiar with common methods and tools for data processing and analysis, and capable of handling large-scale meteorological data.

- Have English literature reading ability, be able to track international cutting-edge technology dynamics, understand the latest research results and development trends in the meteorological field.

3. Comprehensive quality

- Have good team spirit and communication skills, be able to independently carry out work in a team environment, and complete project tasks by collaborating with people of different backgrounds.

- Have strong problem-solving skills and innovative thinking, be able to quickly respond to challenges in the workplace and propose effective solutions.