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Machine Learning Research Engineer / Scientist

SilurianSoftware
Pay
$120K–$250K
per year
Work mode
On-site
Full Time
Location
Education
Master's or PhD

Seattle, WA at a glance

Rent
#8 of 51
$2,980/mo+16% vs US avg
Weather
#39 of 51
184 mild days0 hot · 0 cold
Income tax
#51 of 51
NoneWashington

What you need

PythonMachine Learningdeep learningPyTorch

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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About Silurian

Foundation models to simulate Earth, starting with weather.

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