Hyperbolic Labs

Quantitative Researcher at Hyperbolic Labs (San Francisco, CA)

Hyperbolic Labs· San Francisco, CA·

Role details

Employment
Full-Time

Job description

Who We Are

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.

About the Role

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.

Who You Are

  • 5+ years in quantitative research, trading, or structuring, with hands-on experience building pricing or risk models that were actually traded on, not just backtested
  • Deep fluency in derivatives pricing and hedging — options, futures, forwards — and the ability to reason about instruments where no liquid market or clean volatility surface exists
  • Experience constructing hedges for a portfolio of physical or contracted assets, using both conventional derivatives and non-standard instruments
  • Dynamic pricing expertise: building models that set spot and term prices from supply, demand, and inventory signals in near real time
  • Strong programming skills in Python and comfort working directly with messy production data rather than a curated research dataset
  • Ability to structure new financial products from first principles, including contract design, settlement mechanics, and the assumptions underneath them
  • Clear communicator who can defend a model to finance, engineering, and commercial stakeholders and translate output into a decision
  • Comfortable operating with ambiguity, incomplete data, and no established playbook for the asset class

Preferred Qualifications

  • Experience in commodities, power, or energy markets — the closest existing analogue to compute, with similar delivery, storage, and locational constraints
  • Background in market making, systematic trading, or structuring at a hedge fund, prop shop, bank, or exchange
  • Exposure to nascent or illiquid markets where you had to build the curve rather than consume it
  • Familiarity with GPU compute, AI infrastructure economics, or data center cost structures
  • Experience with crypto or other markets where compute, hashrate, or energy was the underlying
  • Advanced degree in a quantitative field, or equivalent demonstrated depth

Hyperbolic is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Why work at Hyperbolic Labs

  • Culture: Emphasizes “open access, collaboration, innovation, and automation.” Founding story rooted in removing barriers for developers and researchers. [hyperbolic.ai/about]
  • Team: Small (17 employees as of mid-2026), with a flat structure and hands-on roles. Engineering-centric (5 technical staff) plus growing GTM and product teams. [LinkedIn]
  • Remote/Hybrid: HQ in San Francisco; employees across 5 countries – likely offers remote flexibility, though policy not explicitly stated. [LinkedIn]
  • Notable perks: Work on cutting-edge AI infrastructure; direct impact on product; collaboration with top AI labs; use of latest GPUs (H100/H200). [hyperbolic.ai/about]
  • Caution: Recent high-profile departures (co-founder/CTO Yuchen Jin, Head of Business Operations, and a founding AI engineer in April 2026) – candidates should investigate stability and leadership continuity. [LinkedIn]

Application questions