Jax, Pytorch, pre-training large foundation models, self-supervised objectives, large-scale market datasets, time-series foundation models, tokenization schemes, model architectures, data representations, checkpointing, distributed training systems, parallelism, ablations, experiment design, Benchmarking, mixed precision, evaluation optimization, large-model training

probability , Java, Python, Algorithms, data structures, Statistics, AI technologies, calculus, linear algebra