Hiring: Member of Technical Staff - ML Research Engineer, Data Company: Liquid AI Location: San Francisco, CA Job Posted Time: 2026-09-11 10:30:51 Target Skills & Keywords : Computer Vision, Data Pipeline, LLM, PyTorch, Python About the job Experience: •Strong Python skills with the ability to quickly comprehend problems and translate them into clean, working code •Solid ML fundamentals: experience training, evaluating, and iterating on models (PyTorch preferred) •Track record of learning new technical domains quickly •3+ years relevant experience with an M.S., or 1+ year with a Ph.D. (5+ years with a B.S.) Required Skills: •Our Data team powers Liquid Foundation Models across pre-training, vision, audio, and emerging modalities. Public data sources are plateauing. Model performance increasingly depends on purpose-built datasets. We need ML-minded engineers who can collect, filter, and synthesize high-quality data at scale. •We treat data as a research problem, not an infrastructure problem. Our engineers run experiments, design ablations, and measure how data decisions move model quality. We will match you to the team where you can grow the fastest and have the most impact: pre-training, post-training RL, vision-language, audio, or multimodal. •While San Francisco and Boston are preferred, we are open to other locations. •Thinks like a researcher, ships like an engineer: We need people who form hypotheses, run experiments, and measure results. Our engineers understand deep-theoretical research, and our researchers ship production systems. •Learns fast and adapts: We work across modalities that evolve weekly. We need people who pick up new domains quickly and thrive with ambiguity. •Obsesses over data quality: We believe data quality is non-negotiable. Filtering, deduplication, augmentation, and evaluation are first-class concerns for our team, not afterthoughts. •Solves problems independently: Our data engineers sit within training groups (pre-training and multimodal). We collaborate closely, but we expect ownership and self-direction. •Build and maintain data processing, filtering, and selection pipelines at scale Qualifications: •Open-source contributions or publications at NeurIPS, ICML, ICLR, or CVPR •What Success Looks Like (Year One) •You own a critical data pipeline end-to-end for one of our modalities •You have built or improved data systems that measurably moved model performance •You have identified and integrated at least one external dataset that moved the needle Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!