About the job
Who We Are
At Hyperbolic Labs, we are committed to democratizing AI by removing barriers to computing power with our Open-Access AI Cloud. By aggregating global computing resources, we provide an innovative GPU marketplace and AI inference service that ensures both affordability and accessibility. As trailblazers at the convergence of AI and open-source technology, we envision a future where AI innovation is only limited by creativity, not by resource availability. We invite forward-thinking individuals who share our dedication to making AI universally accessible, secure, and affordable. Join us in crafting a platform that empowers innovators worldwide to realize their visionary AI projects.
In anticipation of our growth following our Series A funding, our team — guided by co-founders with advanced degrees in AI, Mathematics, and Computer Science — is set to transform the computing landscape.
About the Role
We are in search of a skilled Site Reliability Engineer to guarantee that Hyperbolic's GPU marketplace and AI infrastructure function with outstanding reliability, performance, and security. As an aggregator of computational resources from numerous global providers, our service level objectives (SLOs), trust, and economic efficiency are critical to our product. Your key responsibilities will include defining and maintaining service level objectives, developing resilient incident response protocols, managing capacity across our extensive GPU network, and implementing secure rollout and rollback mechanisms to ensure uninterrupted platform operation around the clock.
In this influential role, you'll set the reliability benchmarks that foster customer trust in our platform, design comprehensive monitoring and alerting systems for enhanced infrastructure visibility, automate capacity management and resource allocation processes, lead incident response and post-mortem evaluations, and collaborate closely with engineering teams to bolster system resilience. Security and infrastructure hardening will be paramount, necessitating strong isolation protocols between tenants and suppliers, the implementation of effective key management systems, and the establishment of compliance frameworks. This high-impact position will directly affect our ability to deliver on our commitment to providing affordable, accessible AI compute at scale.

