Job description

Payabli is the Intelligent Fintech Operating System for software platforms. If you are a software company, you are a fintech company, and Payabli is your operating system. Built by payments industry and SaaS veterans and powered by its own models, Payabli gives platforms everything they need to embed, manage, and monetize financial services through a single developer-friendly API spanning Pay In, Pay Out, and Pay Ops. Intelligence is not a layer on top, it is the foundation, expressed through Amigo™, Payabli's native AI Agent Suite, and a growing set of capabilities that make payment operations smarter and more autonomous. Payabli gives software companies PayFac capabilities without the heavy lift, administrative burden, or cost of becoming a payment facilitator themselves. With PayFac-as-a-Service, embedded payment acceptance and issuance, and intelligent payment operations, platforms turn payments into a meaningful revenue stream while staying focused on their core product. Payabli is backed by world-class fintech investors including QED Investors, Fika Ventures, TTV Capital, and Bling Capital, and was recently named to the Forbes Fintech 50. For more information, visit payabli.com payabli.com. ABOUT THE ROLE Payabli is looking for a Staff Machine Learning Engineer to set the technical direction for ML at Payabli. A few models are already live and driving real decisions: reducing time-to-clear for risk reviews and scoring transactions and merchants. But that's the starting line, not the destination. We want to build a broad portfolio of models that make payments smarter and easier: automatically choosing the best payment method, reducing disputes and chargebacks, improving authorization rates, forecasting payouts, and more. We need a technical anchor who can both raise the bar on what's live today and stand up many new models from scratch, owning evaluation, monitoring, feature development, retraining, and a clear line from model performance to business impact. The decisions you make in your first quarter (how we build and ship models here, what "good" looks like for ML) will be foundational for years as the function scales. You'll partner closely with product, engineering, and risk operations to find where models create the most leverage across the payments lifecycle and define what "good" means for ML at Payabli. WHAT YOU’LL DO - Set the technical direction for Payabli's model portfolio - both maturing what's live (transaction risk, merchant risk) and building new models across the payments lifecycle (payment method optimization, dispute/chargeback reduction, authorization rate improvement, payout forecasting, and beyond) - Establish the ML foundations the team will build on: experimentation workflows, model monitoring, drift detection, performance benchmarking, and incident response - Translate ambiguous payments problems into well-scoped modeling opportunities, and model performance into business terms (loss rates, approval/auth rates, dispute rates, review efficiency) - Raise the technical bar through influence and example: mentor ML engineers and set practices the future team inherits - Partner with product, engineering, and risk operations to own and prioritize the ML roadmap WHAT WE’RE LOOKING FOR We're looking for someone who meets the minimum requirements below. If you meet them, we encourage you to apply. Your skills and trajectory matter more than checking every box. - 8+ years of ML engineering experience, with 4+ years building and shipping production models that drive real business decisions - A track record of owning modeling architecture and seeing big, hard-to-reverse decisions through to production - Breadth across model types and problem framing. You can stand up a new model in an unfamiliar domain, not just optimize an existing one - Proven experience taking models from prototype to production and owning them post-launch (monitoring, retraining, incident response) - Deep grasp of modeling tradeoffs: precision/recall vs. operational cost, explainability, latency, and regulatory/compliance considerations - Experience establishing ML processes and infrastructure that a growing team inherits - A high technical bar set through influence and example. You make the work and the people around you better, and you're as comfortable in the codebase as in a design review - Ability to communicate model behavior and business impact to non-ML stakeholders - Comfortable in a fast-moving startup environment; bias toward shipping NICE TO HAVES - Payments, fintech, or lending experience: chargebacks, merchant risk, KYC/KYB, authorization/routing, or similar domains. Experience with risk, underwriting, fraud, or credit models specifically is a big plus - Familiarity with AWS ML tools (e.g. SageMaker), and experience with feature stores, training/inference pipelines, and MLOps tooling - An interest in growing into people leadership as the function scales. We expect technical leadership from this role from the start; whether you want to manage a team down the road is genuinely up to you, and there's a clear path if you do. We think you'll love being part of our team because At Payabli, you'll have a front row seat into building a high-growth venture backed fintech company. As a senior leader in Operations, you'll shape how the organization scales and be the driving force behind our AI-first operations strategy — directly influencing how we build, automate, and optimize for the future. You'll stretch yourself every day, learn a ton, grow alongside the company, and have a lot of fun building Payabli with us. We're a values driven company that cares deeply about our team, partners, and customers. Our north star values are: 🤝 Team Love = Customer Love — You understand that when you build great products for your internal partners, they deliver exceptional experiences to merchants. You obsess over the platform partners and businesses that depend on every payout landing on time. 🔥 Run to the Fire — When ACH returns spike or a card program hits a snag, you're the first one in the war room. You don't shy away from hard problems—you chase them. You volunteer for the complex, messy challenges others avoid. 🔍 Little Things Count — You sweat the details because you know a single decimal error in a payout can damage a business. You double-check edge cases, validate every assumption, and understand that excellence lives in the details. 💎 Truth Seekers — You give direct feedback, receive it with grace, and never let ego get in the way of finding the right answer. You document what you don't know, admit mistakes quickly, and hold yourself accountable in the open. 🚀 Relentlessly Curious — You're constantly asking "what if?" and "why not?" You study how competitors solve problems, explore adjacent industries for inspiration, and never stop learning about the payments ecosystem. We build technology that gets noticed and a workplace where people want to grow their careers. Our work has been recognized by some of the industry’s most respected organizations, including being named No. 43 on the 2026 Inc. 5000, marking our third consecutive year on the list. Payabli was also named to the 2026 Forbes Fintech 50, recognizing the most innovative private companies in financial technology, Inc.’s 2025 Best Workplaces, and Built In’s 2026 Best Places to Work in Miami. WHAT WE CAN OFFER YOU - Competitive salary - 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 Payabli is an equal opportunity employer and values a diverse, inclusive workplace. Principals only. No external agency submissions. Candidates must apply directly; We will not accept submissions from third-party recruiters or staffing agencies.

Requirements

Must-haves

Payabli is backed by world-class fintech investors including QED Investors, Fika Ventures, TTV Capital, and Bling Capital, and was recently named to the Forbes Fintech 50.
Establish the ML foundations the team will build on: experimentation workflows, model monitoring, drift detection, performance benchmarking, and incident response
Translate ambiguous payments problems into well-scoped modeling opportunities, and model performance into business terms (loss rates, approval/auth rates, dispute rates, review efficiency)
Raise the technical bar through influence and example: mentor ML engineers and set practices the future team inherits
Partner with product, engineering, and risk operations to own and prioritize the ML roadmap
We're looking for someone who meets the minimum requirements below. If you meet them, we encourage you to apply. Your skills and trajectory matter more than checking every box.
8+ years of ML engineering experience, with 4+ years building and shipping production models that drive real business decisions
A track record of owning modeling architecture and seeing big, hard-to-reverse decisions through to production
Breadth across model types and problem framing. You can stand up a new model in an unfamiliar domain, not just optimize an existing one
Proven experience taking models from prototype to production and owning them post-launch (monitoring, retraining, incident response)
Deep grasp of modeling tradeoffs: precision/recall vs. operational cost, explainability, latency, and regulatory/compliance considerations
Experience establishing ML processes and infrastructure that a growing team inherits
A high technical bar set through influence and example. You make the work and the people around you better, and you're as comfortable in the codebase as in a design review
Ability to communicate model behavior and business impact to non-ML stakeholders
Comfortable in a fast-moving startup environment; bias toward shipping
Competitive salary
Payabli is an equal opportunity employer and values a diverse, inclusive workplace.
Principals only. No external agency submissions. Candidates must apply directly; We will not accept submissions from third-party recruiters or staffing agencies.

Nice-to-haves

Payments, fintech, or lending experience: chargebacks, merchant risk, KYC/KYB, authorization/routing, or similar domains. Experience with risk, underwriting, fraud, or credit models specifically is a big plus
Familiarity with AWS ML tools (e.g. SageMaker), and experience with feature stores, training/inference pipelines, and MLOps tooling
We think you'll love being part of our team because
Relentlessly Curious — You're constantly asking "what if?" and "why not?" You study how competitors solve problems, explore adjacent industries for inspiration, and never stop learning about the payments ecosystem.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

apiaimachine learningmlaws

Platform: ashby
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

401k

Pto

Parental Leave