Liquid AI, Inc
Member of Technical Staff - DevRel
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 obsess over impact, bring relentless care and craftsmanship to building things that truly matter to users You've shipped code that other developers actually use You can explain complex technical concepts without dumbing them down You have strong opinions about what makes foundation models actually useful vs just impressive You understand the difference between research demos and production-ready tools What You'll Actually Do: Developer Experience: Everything from first API call to production deployment needs to feel effortless Technical Content: Demos, tutorials, and reference implementations that make our differentiation tangible Community Presence: Drive community impact, engagement and management through talks, writing, hackathons, and hands-on engagement wherever ML engineers shape the future. Bias for action essential Feedback Loop: Translating real developer friction back to our engineering teams Adoption Metrics: Moving the needle from "interesting research" to "production workloads" You'll be our first line of contact with the developer community, which means you're not just explaining what we've built - you're helping shape what we build next based on how people actually want to use it. The goal isn't just awareness. It's developers choosing us for their next project because the experience is genuinely better What You'll Gain: Engagement with developers, manage community feedback loops, and champion insights that shape Liquid product Building integration examples that solve real problems developers face Writing documentation that assumes intelligence but not telepathy Representing our technical decisions at conferences and in technical forums Working directly with research teams to influence roadmap based on developer needs Creating content that demonstrates why our approach matters for production use cases
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.
While San Francisco and Boston are preferred, we are open to other locations in United States.
This Role Is For You If: You obsess over impact, bring relentless care and craftsmanship to building things that truly matter to users You've shipped code that other developers actually use You can explain complex technical concepts without dumbing them down You have strong opinions about what makes foundation models actually useful vs just impressive You understand the difference between research demos and production-ready tools What You'll Actually Do: Developer Experience: Everything from first API call to production deployment needs to feel effortless Technical Content: Demos, tutorials, and reference implementations that make our differentiation tangible Community Presence: Drive community impact, engagement and management through talks, writing, hackathons, and hands-on engagement wherever ML engineers shape the future. Bias for action essential Feedback Loop: Translating real developer friction back to our engineering teams Adoption Metrics: Moving the needle from "interesting research" to "production workloads" You'll be our first line of contact with the developer community, which means you're not just explaining what we've built - you're helping shape what we build next based on how people actually want to use it. The goal isn't just awareness. It's developers choosing us for their next project because the experience is genuinely better What You'll Gain: Engagement with developers, manage community feedback loops, and champion insights that shape Liquid product Building integration examples that solve real problems developers face Writing documentation that assumes intelligence but not telepathy Representing our technical decisions at conferences and in technical forums Working directly with research teams to influence roadmap based on developer needs Creating content that demonstrates why our approach matters for production use cases
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.