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

About Liquid AI Spun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency, minimal memory usage, privacy, and reliability. We partner with enterprises across consumer electronics, automotive, life sciences, and financial services. We are scaling rapidly and need exceptional people to help us get there.

The Opportunity 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. What We're Looking For We need someone who: Thinks like a researcher, ships like an engineer: You build the pipelines and you make the model-facing calls about what goes into them. You don't hand off either half.

Leads with a hypothesis: Before changing a dataset, you can say what it should do to the model, what you'll measure, and what could fool you, such as contamination or a noisy benchmark. You hold views on pre-training pitfalls, and you test them. Owns problems end to end: You ta