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

The role

You will join the Pre-Training Data team to decide what Liquid Foundation Models learn from by sourcing, filtering, synthesizing, and mixing data. You will run experiments to settle data questions and build pipelines that carry answers into training runs.

What you will do

• Own a part of the pre-training data stack end to end
• Design experiments that show whether a data change helps
• Keep the loop scientifically valid by checking for contamination and benchmark leakage
• Build and run production pipelines that feed real training runs at scale
• Work with pre-training, post-training and eval teammates to propose useful work

Required qualifications

• Hands-on depth in at least one substantial area of pre-training or mid-training data
• Evidence you've connected a data change to a model outcome through an experiment you designed
• Strong Python
• Experience with large-scale data processing
• Practical experience training or fine-tuning models

Nice to have

• PyTorch preferred
• Experience with small or efficient models and how architecture changes affect data strategy
• Long-context data, knowledge distillation, or eval-framework work
• Open-source data tools or datasets with real adoption, or published data research

Benefits

• Competitive base salary plus equity
• Unlimited PTO
• Company-wide Refill Days
• Comprehensive health coverage
• Paid leave for pregnancy, parenting, medical needs, and caring for family

About the company

Spun out of MIT CSAIL, liquid-ai builds general-purpose AI systems that run efficiently across deployment targets. They partner with enterprises across consumer electronics, automotive, life sciences, and financial services.