Deep-Learning Weather Prediction Engineer (H/F)

Country

France

City

PALAISEAU

Area
91 - Essonne

Workplace location

PALAISEAU-LE NEXT(FRA)

Employer company

Total Energies One Tech:

Domain

Research Innovation&Developpt

Type of contract

Regular position

Experience:

Minimum 6 years

Context & Environment

Total Energies has launched an ambitious Integrated Power Modeling initiative designed to secure a leading position in nextgeneration energy systems and electricity markets.

As renewable energy sources are increasingly integrated into power grids andindustries, transportation, and buildings undergo large-scale electrification, the energy landscape is evolving at an unprecedentedpace.

In this context, advanced modeling and forecasting solutions to support supply-demand balance management have become critical enablers of strategic decision-making and long-term competitiveness.

Activities

• Support short and medium-term commercial ambitions in weather forecasting
• Collect and acquire the most relevant datasets both open-source and proprietary tailored to specific geographical areas
• Design and develop robust internal workflows based on deep learning solutions
• Continuously integrate and evaluate the latest models from major tech companies, startups, and academia
• Create educational content adapted for a general audience
• Produce scientific documentation to explain internal developments and contribute to scientific conferences
• Provide support for the adoption and use of internal forecasting tools within the organization
• Conduct both industrial and academic monitoring to stay at the forefront of weather forecasting technologies
• Identify and collaborate with stakeholders at all levels: academia, industry, business units, and programs
• Contribute to team skill development through training, workshops, and knowledge-sharing initiatives

Candidate Profile

• Master's or PhD in deep learning with a specialization in meteorological modeling.
• Hands-on knowledge of deep learning-based weather forecasting models such as Graph Cast, Aurora, and Four Cast Net.
• Hands-on knowledge of the most relevant input data for weather forecasting: meteorological agencies, satellite imagery, and local observations.
• Practical knowledge of the prerequisites for industrializing deep learning.
• Proficiency in computing infrastructures, both cloud and HPC including Slurm, as well as storage architectures.
• More than 6 years of professional experience.
• English and French required.

Additional Information Total Energies values diversity, promotes individual growth and offers equal opportunity careers.

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