Member of Technical Staff, Infrastructure

Member of Technical Staff - InfrastructureIntroductionWe are looking for a Member of Technical Staff - Infrastructure to help build and scale an intelligent, real-time system designed to enhance safety, security, and operational efficiency. As an early engineer, you will play a pivotal role in shaping the foundational infrastructure, ensuring reliability, scalability, and performance in a dynamic environment. If you are comfortable with hands-on development, iterative design, and collaborating closely with a high-caliber team, this role provides the opportunity to make a significant technical impact.About the CompanyBacked by industry leaders from Samsara, Verkada, and Sequoia Capital, this seed-stage startup is advancing intelligent hardware and software solutions for real-time situational awareness. With deep roots in Stanford engineering, the team is focused on deploying cutting-edge AI and cloud infrastructure to deliver a seamless and responsive experience for users. The work is fast-paced, highly technical, and offers the chance to develop first-of-its-kind solutions in the space.About the RoleAs a Member of Technical Staff - Infrastructure, you will be responsible for designing and deploying the backend systems that support large-scale AI applications. This includes optimizing distributed computing workflows, maintaining high-availability services, and ensuring efficient data storage and retrieval. You will work directly with machine learning engineers, software developers, and product teams to create infrastructure that enables rapid iteration and deployment of new capabilities. The ideal candidate has experience working in cloud environments, deploying scalable architectures, and mentoring junior engineers in best practices.What We Can Offer YouCompetitive compensation, including equity in a high-growth startupA collaborative, technical environment that values autonomy and ownershipOpportunity to work on complex AI and machine learning infrastructureAccess to cutting-edge hardware and software tools for developmentStrong engineering culture with mentorship and leadership opportunitiesExposure to real-world AI deployment at scaleKey ResponsibilitiesArchitect and implement cloud infrastructure for large-scale AI workloadsOptimize software and infrastructure for performance, scalability, and reliabilityDevelop automated deployment pipelines for efficient software releasesMaintain and improve distributed systems for data processing and storageMentor junior engineers and contribute to a strong engineering cultureStay informed on emerging technologies and best practices in AI and infrastructureKeywordsCloud computing, Distributed systems, Kubernetes, K8s, Docker, Python, AWS, GCP, PostgreSQL, Scalable InfrastructureHigh-Performance Systems

Created: 2025-02-01