Quantitative Developer, Liquidity

About us Relay is a cross-chain payments protocol that provides instant, low-cost cross-chain bridging, swaps, and transactions. We're the fastest and cheapest way to bridge and transact across chains, serving over 5 million users who have completed 59+ million transactions with $6+ billion in volume across 85+ chains. Our company mission is to make transacting across chains as fast, cheap, and reliable as online payments. We are building the core infrastructure to abstract chains from end user payments, enabling the next billion users to experience the benefits of blockchain without the UX burdens. About the role The Liquidity team keeps Relay's liquidity reliable, competitively priced, capital-efficient, and within its risk framework. Reporting to the Head of Liquidity, you will be one of the first members of this newly formed team, helping define its operating model while owning the day-to-day health of liquidity across assets, chains, wallets, CEXs, bridges, and in-flight rebalances. We are looking for a quantitative generalist who will own the analysis, model development, validation, monitoring, and recommendations that make liquidity decisions rigorous and executable. In this role, you may take on such projects as improving portfolio management and delta-hedging logic, optimizing execution and rebalance costs, and designing a better pricing solution for a client across multiple chains and assets. This is a high-ownership, production-facing role, not a research-only position. You will take ambiguous quantitative problems through analysis, production implementation, monitoring, and live operation, with direct impact on pricing competitiveness, execution quality, P&L, capital efficiency, and risk. We work agentic-first: AI agents accelerate research, analysis, coding, testing, and monitoring, while people remain accountable for methodology, risk, and production decisions. We are looking for candidates who are currently located in or can work full-time in either US West Coast (Pacific Standard Time) or APAC timezones. What you'll do Build portfolio and hedging models Develop portfolio-management and inventory-allocation models across assets, chains, venues, and liquidity systems Develop and recommend target positions, delta-hedging policies, exposure limits, stress responses, and safe hedge-execution logic for approval within the team's liquidity and risk framework Model capital requirements and opportunity costs so liquidity can be allocated where it creates the most value Connect model decisions to realized positions, P&L, capital usage, and risk outcomes Optimize execution and rebalancing Measure execution and rebalance costs across fees, slippage, timing, price impact, and operational failure modes Optimize route choice across bridges, CEXs, single-hop and multi-hop paths, and alternative liquidity providers Develop decision rules for rebalance confidence, route duration, provider enablement, and when not to execute Use live and historical data to improve execution quality, predictability, and capital efficiency Build pricing across assets, chains, and clients Develop client-pricing and fee models across routes, assets, chains, transaction sizes, and market conditions. Design fixed-spread, dynamic-fee, and surge-pricing approaches that remain competitive while covering execution, rebalance, capital, and risk costs. Evaluate pricing for new client requirements and identify low-liquidity routes, exclusions, capacity limits, and required safeguards. Define quantitative inputs for haircuts, seed limits, asset and chain onboarding, and new liquidity mechanisms. Put models into production and operate them Backtest and validate strategies using realistic costs, out-of-sample testing, scenario analysis, stress testing, and clearly stated assumptions Ship model logic with tests, versioned configuration, observability, dry-run evaluation, rollout controls, and human override paths Define the position, flow, execution-lifecycle, P&L, cost, and risk telemetry required to compare decisions with realized outcomes Investigate live pricing anomalies, high price impact, unexpected P&L, balance drift, and model failures; support incidents, rebalances, and approved operational changes when needed Participate in the follow-the-sun on-call rotation, owning quantitative investigation and decision support during your coverage hours and occasionally extending coverage when required About you You're a quantitative generalist who enjoys moving between portfolio, hedging, execution, pricing, and risk problems and is excited to help build a new team's quantitative culture You care about realized outcomes, not only model elegance or backtest performance You're rigorous about assumptions, data quality, uncertainty, and out-of-sample evidence You're comfortable taking high ownership from open-ended analysis through production code, live operation, measurement, and iteration You're willing to switch from planned research to incident analysis or hands-on liquidity operations when the system needs it You explain complex trade-offs clearly to engineering, operations, product, commercial, finance, and leadership partners You're comfortable using AI agents to accelerate research and development while independently validating their output You're excited about crypto, capital markets, and the quantitative challenges of cross-chain liquidity Skills and abilities 3-5+ years in quantitative development, quantitative research, trading, market making, portfolio management, risk, or equivalent applied quantitative work Strong Python and SQL skills, with the engineering judgment to turn analysis and models into tested, maintainable production systems Strong understanding of capital markets and market microstructure, including liquidity, order books, execution costs, slippage, hedging, and risk frameworks Experience evaluating models with realistic costs, incomplete data, changing regimes, and out-of-sample evidence Track record translating ambiguous business or operational questions into measurable objectives, constraints, assumptions, and decision rules Ability to communicate model behavior, uncertainty, risk, and recommendations clearly and operate autonomously within a defined risk framework Nice to have Crypto or blockchain industry experience, particularly with AMMs, bridges, CEXs, stablecoins, and cross-chain liquidity Prior work in electronic trading, execution algorithms, market making, portfolio optimization, treasury, or prime brokerage Experience building production pricing, risk, hedging, or trading systems with real-money consequences Familiarity with simulation infrastructure, model monitoring, P&L attribution, experiment design, and production observability TypeScript experience or a track record working closely with backend engineers to integrate quantitative logic into production services Experience participating in production monitoring, incident response, and hands-on liquidity or trading operations What we offer Competitive base salary Equity package Comprehensive health benefits Unlimited PTO policy with encouraged minimum Remote-first culture with emphasis on collaboration, communication, and flexibility