Quantitative Developer, Liquidity

Relay (Uneven Labs, Inc.)•,

20h•Remote

About The Position

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.

Requirements

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 Haves

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

Responsibilities

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.