Weather Prediction Model Deployment
Budget: $30 – $250 USD
Seeking a skilled Machine Learning Engineer to deploy the GraphCast model for global weather prediction. The tasks involve integrating historical datasets and live data to enable accurate forecasts.
Key Responsibilities:
- Deploy the GraphCast model from Google DeepMind’s repository https://github.com/google-deepmind/graphcast
- Integrate ERA5 datasets and the NOAA Weather API for data inputs.
- Optimize the model for precise 10-day weather predictions.
- Set up deployment on Vultr, ensuring scalability.
- Provide clear and detailed user documentation.
Requirements:
- Proven experience deploying machine learning models in production.
- Proficiency in Python, TensorFlow/PyTorch, and related frameworks.
- Familiarity with ERA5 data and API integration (NOAA Weather API).
- Knowledge of Vultr and cloud infrastructure.
- Excellent model optimization skills for accurate predictions.
Key Responsibilities:
- Deploy the GraphCast model from Google DeepMind’s repository https://github.com/google-deepmind/graphcast
- Integrate ERA5 datasets and the NOAA Weather API for data inputs.
- Optimize the model for precise 10-day weather predictions.
- Set up deployment on Vultr, ensuring scalability.
- Provide clear and detailed user documentation.
Requirements:
- Proven experience deploying machine learning models in production.
- Proficiency in Python, TensorFlow/PyTorch, and related frameworks.
- Familiarity with ERA5 data and API integration (NOAA Weather API).
- Knowledge of Vultr and cloud infrastructure.
- Excellent model optimization skills for accurate predictions.