Member of Technical Staff, Fullstack Engineer

Job not on LinkedIn

September 12

🏄 California – Remote

Although this job is listed in California, this company may be open to hiring remote in other states.

⏰ Full Time

🔴 Lead

🧑‍💻 Full-stack Engineer

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Liquid AI

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Artificial Intelligence • B2B • Enterprise

Liquid AI is a cutting-edge technology company that specializes in edge-native artificial intelligence solutions. Their innovative Liquid Foundation Models (LFMs) are designed to deliver efficient, customizable AI for various environments—from edge computing to cloud infrastructures. By maximizing compute efficiency and leveraging advanced neural network architectures, Liquid AI provides businesses with flexible and powerful AI solutions tailored to their specific needs.

51 - 200 employees

Founded 2023

🤖 Artificial Intelligence

🤝 B2B

🏢 Enterprise

📋 Description

• Architect and implement full-stack solutions for 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 • Contribute to shaping model architectures, scaling dev platforms, and enterprise deployments

🎯 Requirements

• Thrive on building systems from the ground up, not just maintaining them • Understand that good infrastructure is the difference between theoretical and practical ML • Balance pragmatism and ambition—know when to push for scale and when to ship • Excited by the challenge of turning complex ML capabilities into intuitive products • 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

🏖️ Benefits

• 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