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Thermo ML Resident Extropic. 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.. \n. 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.). \n. $75,000 - $150,000 a year. Salary and equity compensation will vary with experience. \n. Extropic is an equal opportunity employer. Please mention the word **IRREPROACHABLE** and tag RMTA0LjE1NC4yMDcuNTI= when applying to show you read the job post completely (#RMTA0LjE1NC4yMDcuNTI=). This is a beta feature to avoid spam applicants. Companies can search these words to find applicants that read this and see they're human..