Research Scientist - Machine Learning
Extropic’s hardware massively accelerates certain kinds of probabilistic inference. Our ML team works on the science of training models in the thermodynamic paradigm, and we are looking for senior research and engineering talent to derive probabilistic ML theory, empirically demonstrate its scaling properties, and deploy performant models. Senior hires will be leading their own research direction and are therefore expected to quickly become experts across our abstraction stack, including the hardware, software, physics, and math.
Responsibilities
Collaborate with senior researchers, residents, engineers, and physicists 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
Create production models for domain experts using customer data
