Job Description
The position involves collaborating with senior engineers to develop and optimize downstream applications based on multi-modal battery models, including various assessment and optimization models. The role requires applying machine learning and deep learning techniques to analyze complex data sets and improve model performance while ensuring data accuracy and consistency.
Key Responsibilities
- Develop downstream applications based on multi-modal battery basic large model
- Participate in the development and optimization of specific application models
- Assist in implementing and optimizing data processing pipelines
- Apply machine learning and deep learning technology for model training, verification, and optimization
- Analyze and process complex data sets to improve model performance
- Assist cross-functional teams in understanding business requirements and developing technical implementation plans
- Track the latest technological developments and introduce cutting-edge methods
Requirements
- Master's degree in computer science, electrical engineering, statistics or related field.
- At least 3 years of practical working experience in machine learning or AI field.
- Familiar with machine learning and deep learning algorithms.
- Proficient in Python, TensorFlow, PyTorch and other commonly used machine learning frameworks and tools.
- Ability to process tabular data, time series data and image data, and can apply these data to specific model development.
- Good communication skills and team spirit, able to effectively work with cross-functional teams.
- Good problem-solving skills and willingness to learn new technologies.
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