Вакансия из Hirify Global, списка международных tech-компаний Для мэтча и отклика нужен Plus
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Зарплата и рынок
Выше среднего
$225к-275к/год
$180к$210кмедиана$270к
По похожим ролям (50) ~ $210к/год
На СНГ рынке: $5.6к/мес ($4.7к - $7.1к)
92
Крутая вакансия
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Роль первого ML-инженера в быстрорастущем финтехе с очень высокой зарплатой и возможностью создать инфраструктуру с нуля.
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Высокая зарплатаТрендовый доменБыстрый ростБольшое влияниеСовременный стекГибкий график
Оценка от Hirify AI
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Описание вакансии
Текст:
Hirify AI/Оригинал
TL;DR
Machine Learning Lead (Fintech): Building and deploying fraud detection and risk decisioning models for high-volume payment flows with an accent on transaction data, feature engineering, and acquiring-side payments fraud. Focus on owning the full model lifecycle, integrating external fraud partners, and establishing scalable MLOps and ML practices.
Location: Chicago, United States; on-site
Salary: $225,000–$275,000 USD base salary per year, plus performance bonus and equity.
Company
hirify.global is a fintech payment service provider using stablecoins, AI-driven fraud prevention, instant settlement, global pay-ins, multi-currency FX, and unified payouts for marketplaces, fintechs, remittance providers, gaming platforms, and ecommerce merchants.
What you will do
Lead the first dedicated ML team and own the fraud and risk intelligence layer.
Build, deploy, monitor, and iterate production fraud models using transaction and behavioral data.
Define and track fraud and risk metrics, including detection rate, false positive rate, chargeback rate, and dispute win rate.
Discover emerging fraud signals and attack patterns across global payment methods.
Partner with Engineering, Product, and Operations to embed fraud intelligence into payment flows and internal tooling.
Requirements
5+ years of experience in machine learning, applied data science, or production ML.
Demonstrated experience building fraud models on the acquiring side of payments, such as at an acquirer, PSP, or payment facilitator.
Experience taking ML projects from proof of concept through production deployment.
Strong knowledge of authorization fraud, card-not-present fraud, friendly fraud, chargebacks, merchant risk, statistics, and feature engineering on high-volume financial data.
Ability to own ambiguous problems end-to-end and collaborate across Engineering, Product, and Operations.
Nice to have
Experience at an acquirer, ISO, PayFac, or payments infrastructure company.
Experience scaling MLOps pipelines, retraining schedules, and real-time monitoring systems.
Familiarity with card network rules, dispute workflows, fraud liability frameworks, and real-time fraud scoring.
Experience as an early or sole ML hire, or with stablecoin, crypto, and alternative payment rails.
Culture & Benefits
Opportunity to build core fraud and risk infrastructure during a rapid growth phase.
Competitive compensation with performance bonus and meaningful ownership.
Health and wellness benefits.
401(k) savings plan and flexible time off.
Collaborative and innovative work environment with direct impact on company direction.
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