Liquid AI
Member of Technical Staff - Post Training Data
Liquid AI, San Francisco, California, United States, 94199
Member of Technical Staff - Post Training Data
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Member of Technical Staff - Post Training Data
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Liquid AI
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.
Seniority level Mid‑Senior level
Employment type Full‑time
Job function Engineering and Information Technology
#J-18808-Ljbffr
Member of Technical Staff - Post Training Data
role at
Liquid AI
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.
Seniority level Mid‑Senior level
Employment type Full‑time
Job function Engineering and Information Technology
#J-18808-Ljbffr