Liquid AI, Inc
Member of Technical Staff - Fullstack Engineer
Liquid AI, Inc, San Francisco, California, United States, 94199
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.
This Role Is For You If: You thrive on building systems from the ground up, not just maintaining them You understand that good infrastructure is the difference between theoretical and practical ML You balance pragmatism and ambition-knowing when to push for scale and when to ship You're excited by the challenge of turning complex ML capabilities into intuitive products Desired Experience: Proven track record of architecting and scaling systems from scratch Deep understanding of modern software architecture and best practices Experience deploying ML-powered systems in real-world production environments Strong opinions about engineering practices-backed by hard-earned lessons Ability to decide when to build vs. when to leverage existing tools What You'll Actually Do: Architect and implement full-stack solutions for both internal platforms and customer-facing products Design and scale backend services that enable robust ML model deployment Build deployment infrastructure that runs seamlessly across cloud and on-premise environments Develop interfaces that make complex ML systems accessible and usable Establish workflows that accelerate ML research-to-deployment cycles Collaborate closely with Product and ML teams to iterate quickly and effectively What You'll Gain: The chance to architect foundational systems at a true greenfield stage Direct collaboration with exceptional ML researchers and product builders Influence over critical technical decisions that will define Liquid's trajectory The opportunity to shape how enterprises deploy efficient AI models at scale 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.
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.
This Role Is For You If: You thrive on building systems from the ground up, not just maintaining them You understand that good infrastructure is the difference between theoretical and practical ML You balance pragmatism and ambition-knowing when to push for scale and when to ship You're excited by the challenge of turning complex ML capabilities into intuitive products Desired Experience: Proven track record of architecting and scaling systems from scratch Deep understanding of modern software architecture and best practices Experience deploying ML-powered systems in real-world production environments Strong opinions about engineering practices-backed by hard-earned lessons Ability to decide when to build vs. when to leverage existing tools What You'll Actually Do: Architect and implement full-stack solutions for both internal platforms and customer-facing products Design and scale backend services that enable robust ML model deployment Build deployment infrastructure that runs seamlessly across cloud and on-premise environments Develop interfaces that make complex ML systems accessible and usable Establish workflows that accelerate ML research-to-deployment cycles Collaborate closely with Product and ML teams to iterate quickly and effectively What You'll Gain: The chance to architect foundational systems at a true greenfield stage Direct collaboration with exceptional ML researchers and product builders Influence over critical technical decisions that will define Liquid's trajectory The opportunity to shape how enterprises deploy efficient AI models at scale 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.