Staff Machine Learning Engineer

🕒 September 4

🇺🇸 United States – Remote

⏰ Full Time

🔴 Lead

🤖 Machine Learning Engineer

👻 Ghost score 12%

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Payabli

WebsiteLinkedInAll Job Openings

11 - 50 employees

💼 Consulting

📦 Logistics

💳 Fintech

💰 $4.1M Seed Round on 2022-04

Consulting • Logistics • Fintech

Payabli is a next-generation payments infrastructure company that specializes in enabling Software as a Service (SaaS) providers and other businesses to easily embed and monetize payments. The company offers a unified API and infrastructure stack that supports the full lifecycle of payments businesses, including payment acceptance (Pay In), vendor payouts (Pay Out), and payment operations (Pay Ops). Payabli provides solutions such as managed payables, on-demand payouts, spend management, boarding, underwriting, risk management, billing engine, reporting, and compliance. With a focus on API-first capabilities, Payabli allows its partners to build world-class payments offerings that are fully integrated into their product experience. The company serves various partners and industries, including financial institutions and affiliate partners, offering strategic advisory and cost analysis services to optimize interchange and payments solutions.

📋 Description

• Set the technical direction for Payabli's model portfolio, maturing live transaction and merchant risk models and building new models across the payments lifecycle • Establish experimentation workflows, model monitoring, drift detection, performance benchmarking, and incident response foundations • Translate ambiguous payments problems into well-scoped modeling opportunities • Connect model performance to business metrics such as loss rates, approval/auth rates, dispute rates, and review efficiency • Mentor ML engineers and establish practices for the future team • Partner with product, engineering, and risk operations to own and prioritize the ML roadmap

🎯 Requirements

• 8+ years of ML engineering experience, with 4+ years building and shipping production models that drive real business decisions • Track record of owning modeling architecture and seeing big, hard-to-reverse decisions through to production • Breadth across model types and problem framing; ability to stand up a new model in an unfamiliar domain • Proven experience taking models from prototype to production and owning them post-launch, including monitoring, retraining, and incident response • Deep grasp of modeling tradeoffs including precision/recall vs. operational cost, explainability, latency, and regulatory/compliance considerations • Experience establishing ML processes and infrastructure that a growing team inherits • Ability to communicate model behavior and business impact to non-ML stakeholders • Comfortable in a fast-moving startup environment • Familiarity with AWS ML tools such as SageMaker, feature stores, training/inference pipelines, and MLOps tooling is a nice to have • Payments, fintech, or lending experience is a nice to have • Interest in growing into people leadership is a nice to have • Must be legally authorized to work in the United States • Must apply directly; no third-party recruiter or staffing agency submissions

🏖️ Benefits

• Stock options with the potential to unlock more equity as we grow • Flexible PTO and paid parental leave • Medical, dental, & vision insurance • 401K, HSA, pre-tax savings programs • Competitive salary

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