A machine learning engineer researches and prototypes novel neural network architectures (e.g., alternatives to Transformers, RNNs, state-space models), designing experiments on scaling, memory, and compute trade-offs and working with inference/systems engineers to make research deployable. Core stack is research-oriented ML code in PyTorch or JAX.
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