Hiring: Member of Technical Staff - GPU Infrastructure Engineer Company: Liquid AI Location: San Francisco, CA Job Posted Time: 2026-09-11 10:30:51 Target Skills & Keywords : Hadoop, Kubernetes, Linux About the job Experience: •Strong software engineering experience, with the ability to build production-quality infrastructure tooling and automation. •Deep knowledge of distributed systems, Linux, networking, and storage. •A track record of supporting production users and turning recurring failures into durable solutions. •The technical depth to partner effectively with senior research and infrastructure engineers. Required Skills: •Our Cluster Infrastructure team owns the compute environments that power foundation model training and research at Liquid AI. We are looking for a hands-on software engineer to keep our GPU clusters reliable, improve resource efficiency, and build the tooling that allows researchers to focus on model development rather than infrastructure. •Brings order to complex systems: You identify root causes and build durable fixes rather than repeatedly firefighting. •Is an engineer first: You can go deep across Linux, networking, storage, schedulers, and distributed systems. •Balances operations and engineering: You handle urgent issues while steadily replacing manual work with automation. •Owns outcomes: You communicate clearly, prioritize effectively, and drive problems to resolution across internal teams and external providers. •Own the reliability and operation of the GPU clusters used for training and research. •Debug issues across compute, storage, networking, schedulers, and distributed workloads. •Improve CPU, GPU, and storage utilization through better tooling and automation. Qualifications: •What Success Looks Like (Year One) •Researchers spend less time resolving infrastructure and resource-allocation issues. •GPU, CPU, and storage resources are used more efficiently across the fleet. •Recurring operational problems are replaced with automation, monitoring, and dependable platform tooling. •Liquid AI has the beginnings of a durable internal platform that hides infrastructure complexity from researchers. Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!