Thermodynamic ML Research Resident — Flexible

Extropic; California (PA); On-site; USD 42,000 - 60,000; Part time

Job summary

Extropic is seeking junior ML scientists to join our residency program on a part-time or full-time basis. This flexible program offers autonomy beyond typical internships and focuses on advancing probabilistic inference and energy-based models.

Residents will collaborate with senior researchers to develop theory, scale experiments, publish findings, and contribute to open-source efforts, with exposure to cutting-edge hardware teams.

Qualifications

• Experience in scientific Python 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.

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

Skills

Scientific Python

Probabilistic modeling

Linear algebra

Applied ML projects

Research communication

Tools

PyTorch

TensorFlow

Job description

Extropic is seeking junior ML scientists to join our residency program on a part-time or full-time basis. This flexible program offers autonomy beyond typical internships and focuses on advancing probabilistic inference and energy-based models.

Residents will collaborate with senior researchers to develop theory, scale experiments, publish findings, and contribute to open-source efforts, with exposure to cutting-edge hardware teams.