6+ years of professional experienceindevelopingdeeplearning models
An advanced degree (MS/PhD) in a STEM field, or added years of deep industry experience
Algorithmic reasoningshould be second nature (e.g.,data structuresand computational complexity)
Ability toquickly digestresearch papers and implement methods
Abreadth of knowledge ingenerativemachine learning paradigms(e.g.,energy-based models,flow-basedmodels,autoregressive models)complemented by a depth of knowledge in several subdomains
Strong problem-solving, communication, and collaboration skills
Familiarity with Monte Carlo methods (e.g.,Metropolis-Hastings, Gibbs,paralleltemperingand sequential Monte Carlo)
A solid understanding ofBoltzmann Machines(i.e.,Ising models,Markovrandomfields,exponentialfamily distributions)
Familiarity with probabilistic graphical models
Familiarity with annealingand gate-basedquantum computers
Expertisewith C++ orotherlow-level programming languages
Contributions to open-source software
Familiarity withMLOpsecosystems (e.g., Kubeflow,VertexAI, Airflow)
Experience indelivering end-to-end software projects---from architectto deployment
Expertisein building extensible APIs and frameworks aroundPyTorch(or, e.g., JAX and TensorFlow)