Role Overview
We are seeking Machine Learning Research Engineers / Scientists to join our team working on groundbreaking physics foundation models. The successful candidate will develop, train and deploy to production large-scale AI foundation models for weather and energy.

What You'll Do
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 optimisation 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.

We expect you to have
Proven track record in developing and deploying deep learning models.
Advanced proficiency in Python and modern ML frameworks (PyTorch, TensorFlow, Jax).
Demonstrated experience with distributed training systems and large-scale data pipelines.
Strong software engineering practices and system design principles.
Excellent problem-solving and analytical skills.
Outstanding communication and collaboration abilities.

Nice to have
MSc or PhD in Artificial Intelligence, Computer Science, or related technical field.
Published research in prestigious AI conferences/journals (NeurIPS, ICML, etc.).
Hands-on experience with one or several of the following: transformers, diffusion models, self-supervised learning, foundation model training/fine-tuning.

Join us in pushing the boundaries of physics foundation models!

Machine Learning Researcher | Python | PyTorch | Machine Learning | Deep Learning | Hybrid, Seattle, WA

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