Silurian
Foundation models to simulate Earth, starting with weather.
What Silurian does
Silurian is building foundation models for simulating Earth, starting with weather. From assessing the risk of wildfires to predicting the energy grid load, we provide an infrastructure layer for our planet. Our frontier models push the boundaries of what can be simulated on Earth and improve decision making across vital sectors including energy, insurance, agriculture, and logistics.
1 open role
What the role involves
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, energy, and beyond. 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 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. We expect you to have 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. 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 foundation models for the physical world!
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Company facts compiled from public sources and last refreshed 9 September 2026. Details change; treat the company’s own site as the authority.