Hyperbolic Labs is on a mission to democratize AI by breaking down the barriers to computing power with our Open-Access AI Cloud. By making better use of idle computing resources across the globe, we offer an innovative GPU marketplace and AI inference service that promise affordability and accessibility for all. As pioneers at the intersection of AI and open-source technology, we believe in an open future where AI innovation is limited only by imagination, not by access to resources. We're looking for forward-thinking individuals who share our passion for making AI universally accessible, secure, and affordable. Join us in building a platform that empowers innovators everywhere to turn their visionary AI projects into reality.
Compute is becoming a traded asset, and almost none of the market structure exists yet. There is no settled forward curve, no standard contract, no consensus on how to price optionality on a GPU-hour. We're building the financial layer of our marketplace, and we're looking for a Quantitative Researcher to own the modeling behind it.
You'll build the pricing models that set spot and term rates dynamically across GPU types and regions, hedge our compute portfolio using both conventional derivatives and non-traditional instruments, and design the options and futures structures that let customers and suppliers transfer compute risk. You'll also be our read on the market — where pricing is heading, what's tradable, and what we should be building next. This is early, unmapped work: you'll be defining the methodology rather than applying an existing one.
Hyperbolic is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Hyperbolic provides high‑performance GPU clusters and managed inference for AI startups and ML teams that need reliable capacity on demand, at a lower cost than anyone else.
Researchers use Hyperbolic to launch new models faster, avoid GPU waitlists, and scale from prototype to production on the same platform for both training and inference.