Member of Technical Staff - ML Research Engineer, Pre-Training Data

You'll join the Pre-Training Data team, which decides what Liquid Foundation Models learn from: which data we source, filter, synthesize, and mix, and in what order. Public data sources are plateauing, so model quality increasingly depends on purpose-built datasets and on knowing which data changes actually help.

We treat data as a research problem, not an infrastructure problem. You'll work alongside our pre-training researchers on a small team, run the experiments that settle data questions, and build the pipelines that carry the answers into training runs.

The work

• Own a part of the pre-training data stack end to end, for example a quality filter, a dedup or decontamination pass, a synthetic or distillation data source, or a mixture or curriculum experiment, from question to shipped result.
• Design experiments that show whether a data change helps: