{"id":3437280,"url":"https://alion.io/job/unevenlabs-quantitative-developer-liquidity","title":"Quantitative Developer, Liquidity","company":{"id":4476545,"name":"Uneven Labs","domain":"unevenlabs.com","url":"https://alion.io/company/unevenlabs","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Kula","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"middle","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":{"label":"UTC-8 – UTC+10","utc_offset_min":-8,"utc_offset_max":10},"hiring_geo_confidence":"structured","locations":[],"countries":[],"hiring_countries":["US"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":91000,"max_usd":169000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":108},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"AI Agents","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"TypeScript","optional":true}],"status":"closed","first_seen_at":"2026-10-28T03:39:20Z","employer_posted_date":"2026-10-28","last_verified_at":"2026-10-30T06:10:21Z","board_verified":false,"closed_at":"2026-10-30T06:10:21Z","days_open":2,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":2},"description":"About us\nRelay 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.\nOur 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.\nAbout the role\nThe 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.\nWe 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.\nThis 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.\nWe are looking for candidates who can work full-time in either PST (UTC -8) or APAC timezones.\nWhat you'll do\nBuild portfolio and hedging models\nDevelop portfolio-management and inventory-allocation models across assets, chains, venues, and liquidity systems\n\nDevelop 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\n\nModel capital requirements and opportunity costs so liquidity can be allocated where it creates the most value\n\nConnect model decisions to realized positions, P&L, capital usage, and risk outcomes\n\nOptimize execution and rebalancing\nMeasure execution and rebalance costs across fees, slippage, timing, price impact, and operational failure modes\n\nOptimize route choice across bridges, CEXs, single-hop and multi-hop paths, and alternative liquidity providers\n\nDevelop decision rules for rebalance confidence, route duration, provider enablement, and when not to execute\n\nUse live and historical data to improve execution quality, predictability, and capital efficiency\n\nBuild pricing across assets, chains, and clients\nDevelop client-pricing and fee models across routes, assets, chains, transaction sizes, and market conditions.\n\nDesign fixed-spread, dynamic-fee, and surge-pricing approaches that remain competitive while covering execution, rebalance, capital, and risk costs.\n\nEvaluate pricing for new client requirements and identify low-liquidity routes, exclusions, capacity limits, and required safeguards.\n\nDefine quantitative inputs for haircuts, seed limits, asset and chain onboarding, and new liquidity mechanisms.\n\nPut models into production and operate them\nBacktest and validate strategies using realistic costs, out-of-sample testing, scenario analysis, stress testing, and clearly stated assumptions\n\nShip model logic with tests, versioned configuration, observability, dry-run evaluation, rollout controls, and human override paths\n\nDefine the position, flow, execution-lifecycle, P&L, cost, and risk telemetry required to compare decisions with realized outcomes\n\nInvestigate live pricing anomalies, high price impact, unexpected P&L, balance drift, and model failures; support incidents, rebalances, and approved operational changes when needed\n\nParticipate in the follow-the-sun on-call rotation, owning quantitative investigation and decision support during your coverage hours and occasionally extending coverage when required\n\nAbout you\nYou'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\n\nYou care about realized outcomes, not only model elegance or backtest performance\n\nYou're rigorous about assumptions, data quality, uncertainty, and out-of-sample evidence\n\nYou're comfortable taking high ownership from open-ended analysis through production code, live operation, measurement, and iteration\n\nYou're willing to switch from planned research to incident analysis or hands-on liquidity operations when the system needs it\n\nYou explain complex trade-offs clearly to engineering, operations, product, commercial, finance, and leadership partners\n\nYou're comfortable using AI agents to accelerate research and development while independently validating their output\n\nYou're excited about crypto, capital markets, and the quantitative challenges of cross-chain liquidity\n\nSkills and abilities\n3-5+ years in quantitative development, quantitative research, trading, market making, portfolio management, risk, or equivalent applied quantitative work\n\nStrong Python and SQL skills, with the engineering judgment to turn analysis and models into tested, maintainable production systems\n\nStrong understanding of capital markets and market microstructure, including liquidity, order books, execution costs, slippage, hedging, and risk frameworks\n\nExperience evaluating models with realistic costs, incomplete data, changing regimes, and out-of-sample evidence\n\nTrack record translating ambiguous business or operational questions into measurable objectives, constraints, assumptions, and decision rules\n\nAbility to communicate model behavior, uncertainty, risk, and recommendations clearly and operate autonomously within a defined risk framework\n\nNice to have\nCrypto or blockchain industry experience, particularly with AMMs, bridges, CEXs, stablecoins, and cross-chain liquidity\n\nPrior work in electronic trading, execution algorithms, market making, portfolio optimization, treasury, or prime brokerage\n\nExperience building production pricing, risk, hedging, or trading systems with real-money consequences\n\nFamiliarity with simulation infrastructure, model monitoring, P&L attribution, experiment design, and production observability\n\nTypeScript experience or a track record working closely with backend engineers to integrate quantitative logic into production services\n\nExperience participating in production monitoring, incident response, and hands-on liquidity or trading operations\n\nWhat we offer\nCompetitive base salary\n\nEquity package\n\nComprehensive health benefits\n\nUnlimited PTO policy with encouraged minimum\n\nRemote-first culture with emphasis on collaboration, communication, and flexibility","description_format":"text","description_chars":7211,"description_truncated":false,"requirements":{"experience_years_min":3,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Equity","Unlimited PTO"],"hiring_locations":[{"name":"United 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