Member of Technical Staff - Post Training Data

Work With Us

At Liquid, we’re not just building AI models—we’re redefining the architecture of intelligence itself. Spun out of MIT, our mission is to build efficient AI systems at every scale. Our Liquid Foundation Models (LFMs) operate where others can’t: on-device, at the edge, under real-time constraints. We’re not iterating on old ideas—we’re architecting what comes next.

We believe great talent powers great technology. The Liquid team is a community of world-class engineers, researchers, and builders creating the next generation of AI. Whether you're helping shape model architectures, scaling our dev platforms, or enabling enterprise deployments—your work will directly shape the frontier of intelligent systems.

While San Francisco and Boston are preferred, we are open to other locations in United States.

This Role Is For You If:

• You want to play a hands-on role in shaping the next generation of Liquid Foundation Models (LFMs)

• You have a passion for data quality — building high-fidelity post-training datasets that elevate model performance

• You care about craftsmanship: from dataset design to code structure, you take pride in precision and impact

Required Experience:

• Education & Experience: B.S.+ 5 years, M.S.+ 3 years, or Ph.D.+ 1 year of relevant experience

• Dataset Engineering: Proven ability in data curation, cleaning, augmentation, and synthetic data generation

• Machine Learning: Experience working with LLMs; able to write and debug models in major ML frameworks

• Software Development: Strong Python skills with an emphasis on clean, maintainable, and scalable code

Desired Experience:

• Deep understanding of data quality and how it impacts model behavior

• Experience fine-tuning or customizing LLMs for specific objectives

• Contributions to open-source ML or data projects

• M.S. or Ph.D. in Computer Science, Electrical Engineering, Mathematics, or related field

What You'll Actually Do:

• Analyze model failure modes to identify and close data gaps

• Design and implement pipelines for generating and validating training datasets

• Fine-tune models and run targeted ablations to test dataset improvements

• Collaborate with a world-class ML engineering team and contribute best practices for data quality and experimentation

What You'll Gain:

• The opportunity to work directly on state-of-the-art AI systems at one of the most advanced AI companies in the world

• A fast-paced, collaborative environment where your work has direct impact on model performance and product capability

• The satisfaction of knowing your data craftsmanship helps define the next frontier in AI

About Liquid AI

Spun out of MIT CSAIL, we’re a foundation model company headquartered in Boston. Our mission is to build capable and efficient general-purpose AI systems at every scale—from phones and vehicles to enterprise servers and embedded chips. Our models are designed to run where others stall: on CPUs, with low latency, minimal memory, and maximum reliability. We’re already partnering with global enterprises across consumer electronics, automotive, life sciences, and financial services. And we’re just getting started.