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Salary
$120k – $250k per year
Location
In office (Seattle)
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 18, 2026. First seen by Alion on Aug 30, 2026.

Overview
Company
Impact
Profile match
Silurian AI is an artificial intelligence company that builds foundation models simulating the physical systems of the Earth, starting with weather forecasting. Its Generative Forecasting Model produces high-resolution forecasts for customers exposed to extreme weather risk, among them energy and insurance companies. It was founded in 2024 by researchers who had worked on large-scale weather models at Microsoft. The company is headquartered in Seattle, Washington, United States.

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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