Liquid AI, Inc.
Member of Technical Staff - Backend 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.
While San Francisco and Boston are preferred, we are open to other locations in United States.
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.
#J-18808-Ljbffr
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 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.
#J-18808-Ljbffr