Extropic Thermo ML Resident

via RemoteOK

Overview

Extropic is looking for junior ML scientists to join our residency program on either a part-time or full-time basis.  Our hardware massively accelerates certain kinds of probabilistic inference, and residents will help pioneer the science of training models in the thermodynamic paradigm.


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Responsibilities
  • Collaborate with senior researchers to derive the theory of new probabilistic models and their learning rules, including energy-based models and diffusion models
  • Scale up experimentation infrastructure and optimize over the design space of models
  • Implement, visualize, and evaluate new architectures, training algorithms, and benchmarks
  • Publish papers, contribute to open source, and communicate design insights to our hardware team


Required Qualifications
  • Experience in scientific Python
  • Experience with JAX or similar deep learning framework (PyTorch, TensorFlow, or Keras)
  • Strong foundations in probability and linear algebra
  • Projects or papers demonstrating hands-on experience in applied machine learning and data science
  • Familiarity with deep learning theory and literature, including theory of over-parameterization and scaling laws


Preferred Qualifications
  • Experience training energy-based models (EBMs) or diffusion models
  • Experience with graph neural networks (GNNs) or graph message passing algorithms
  • Experience with infrastructure for deep learning experimentation and training (Slurm, Ray, Kubernetes, Weights & Biases, etc.)
  • Strong theoretical background in information geometry
  • Strong grasp of computational Bayesian methods, including MCMC sampling methods and variational inference
  • Publications in top ML conferences (NeurIPS, ICML, ICLR, CVPR, etc.)


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$75,000 - $150,000 a year
Salary and equity compensation will vary with experience
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Extropic is an equal opportunity employer



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Posted Extropic Thermo ML Resident on February 21, 2025 via RemoteOK

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