Develop, train and deploy to production large-scale AI foundation models for weather, energy, and beyond.
Requirements
- Proven track record in developing and deploying deep learning models.
- Advanced proficiency in Python and modern ML frameworks (PyTorch, Jax or similar).
- Demonstrated experience with distributed training systems and large-scale data pipelines.
- Strong software engineering practices and system design principles.
- Hands-on experience with one or several of the following: transformers, diffusion models, self-supervised learning, foundation model training/fine-tuning.
Responsibilities
- Architect and implement innovative ML models for complex spatiotemporal data analysis.
- Lead end-to-end development of large-scale AI systems, from research to production.
- Drive the optimization of training and inference pipelines for maximum performance.
- Conduct validation experiments and performance analysis.
- Spearhead long-term research initiatives with significant real-world impact.
- Collaborate with world-class researchers and engineers.
Other
- Excellent problem-solving and analytical skills.
- Outstanding communication and collaboration abilities.
- MSc or PhD in Artificial Intelligence, Computer Science, or related technical field.
- Published research in prestigious AI conferences/journals (NeurIPS, ICML, etc.).
