We train on trajectories that can span weeks or months. Dense attention makes those horizons infeasible, and context compression is not enough for reliable memory.
This role develops fixed-size state architectures for models trained on long-horizon computer-use trajectories.
Test scaling behavior.
Study failure modes such as state collapse and loss of long-range dependencies.
Publish the results.
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