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Machine Learning Researcher | Python | PyTorch | Machine Learning | Deep Learning | Hybrid, Sea

Job in Seattle, King County, Washington, 98127, USA
Listing for: Enigma
Full Time position
Listed on 2026-02-16
Job specializations:
  • Business
    Artificial Intelligence, Data Scientist
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below
Position: Machine Learning Researcher | Python | PyTorch | Machine Learning | Deep Learning | Hybrid, Sea[...]

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, Tensor Flow, 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.
Ncie 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!

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