SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Hyperbolic Labs is building the financial infrastructure layer for a GPU marketplace and AI inference service. As a Quantitative Researcher, you will own the modeling behind dynamic pricing and risk management for compute as a traded asset.
You'll develop pricing models that set spot and term rates dynamically across GPU types and regions, design hedging strategies for the compute portfolio using both conventional derivatives and non-traditional instruments, and structure options and futures products that enable customers and suppliers to transfer compute risk. You'll serve as the market intelligence function—identifying pricing trends, tradable opportunities, and product development priorities.
This is foundational work in an emerging asset class. You'll define methodology from first principles rather than apply established frameworks. The role requires building models that actually trade in production, not just backtest, and translating quantitative output into decisions for finance, engineering, and commercial teams.
Required: 5+ years in quantitative research, trading, or structuring with hands-on experience in pricing or risk models deployed to live markets. Deep expertise in derivatives pricing and hedging (options, futures, forwards), including instruments without liquid markets or clean volatility surfaces. Experience constructing hedges for physical or contracted asset portfolios using both standard and non-standard derivatives. Strong dynamic pricing background—building models that set prices from supply, demand, and inventory signals in near real-time. Proficiency in Python and comfort working with messy production data. Ability to structure financial products from first principles, including contract design and settlement mechanics. Clear communication skills to defend models to diverse stakeholders. Comfort with ambiguity, incomplete data, and novel asset classes.
Preferred: Background in commodities, power, or energy markets (closest analogue to compute). Experience in market making, systematic trading, or structuring at hedge funds, prop shops, banks, or exchanges. Exposure to nascent or illiquid markets where you built curves rather than consumed them. Familiarity with GPU compute, AI infrastructure economics, or data center costs. Crypto or energy-market experience. Advanced degree in quantitative field or equivalent demonstrated depth.
