alpha generation , Jax, Pytorch, Execution, pre-training large foundation models, transfer across instruments, self-supervised objectives, evaluation protocols, model-serving components, market making, data efficiency, large-scale market datasets, time-series foundation models, tokenization schemes, model architectures, data representations, distributed training recipes, risk-management tasks, scaling laws, regime robustness, training checkpointing, Pricing

Apis, concurrency, Memory Management, Distributed Systems, data structures, Python, Execution, performance profiling, backtesting, market-data feature-computation, Simulation, Monitoring, low-latency systems, production debugging, model-serving