Extras · 1 of 4

A typical day

Stand-up with the team, then experiments: preparing training data, tuning a model, waiting for it to train, reading the results. Writing the code that serves the model inside a product and monitoring it once it is live. Reading a new paper because the field changed again last week. Meetings with product managers about what the model is allowed to get wrong. Compute costs are always a topic.