Part-Time Thermo ML Resident

OverviewExtropic seeks junior ML scientists for a residency program, part-time or full-time. Our hardware accelerates probabilistic inference. Residents will advance training models in the thermodynamic paradigm.

Responsibilities

• Collaborate with senior researchers to develop probabilistic models and learning rules (energy-based models, diffusion models).
• Scale up experimentation infrastructure and optimize model design.
• Implement, visualize, and evaluate new architectures, training algorithms, and benchmarks.
• Publish papers, contribute to open source, and share design insights with the hardware team.

Required Qualifications

• Experience in scientific Python
• Proficiency with JAX or similar deep learning frameworks (PyTorch, TensorFlow, or Keras)
• Strong probability and linear algebra foundations
• Projects/papers showcasing applied machine learning and data science experience
• Familiarity with deep learning theory and literature, including 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
• Familiarity with deep learning experimentation and training infrastructure (Slurm, Ray, Kubernetes, Weights & Biases, etc.)
• Strong theoretical background in information geometry
• Understanding of computational Bayesian methods, including MCMC sampling and variational inference
• Publications in top ML conferences (NeurIPS, ICML, ICLR, CVPR, etc.)

Salary and Equity

Compensation varies with experience, $75,000 - $150,000 per year.

Equal Opportunity Employer

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