ML Ops Engineer

As an MLOps Engineer at Coinflow, you own the platform that takes our fraud, risk, and payments models from notebook to production. You build the pipelines, serving infrastructure, and monitoring that let us score every transaction in real time and retrain safely. Our models sit in the authorization path of real money, so latency, reliability, and explainability matter as much as accuracy.

What you'll do

• Build and operate the real-time inference layer that scores transactions in the authorization path, meeting tight latency budgets, designing safe fallbacks when a model or feature is unavailable, and ensuring model outages never become payments outages
• Own training, validation, and deployment pipelines end to end, building reproducible feature pipelines from transaction, device, and chargeback data with point-in-time correctness so offline training matches online scoring
• Make model shipping straightforward by owning versioning, registries, shadow mode, champion/challenger testing, canary rollouts, and one-click rollback, with every change gated by evals
• Instrument models for monitoring the way you instrument services, tracking latency, score distributions, feature drift, approval rates, and fraud and chargeback outcomes, wired into the observability stack with alerts on real problems
• Integrate and evaluate external fraud and risk vendors alongside your own models through parallel and shadow testing, comparing performance on your data to give the team clear guidance on what to trust
• Power the data and scoring behind merchant-facing risk products so merchants can see risky customers and set their own blocking rules on top of your signals

What you bring

• 4+ years in MLOps, ML infrastructure, or ML platform engineering, ideally at a fintech, payments company, or other regulated environment
• Production experience running models with real latency and uptime requirements, particularly in a transaction or decisioning path
• Strong Python skills and solid production engineering habits; comfortable reading and writing TypeScript/Node since that is where most services live
• Hands-on experience with ML pipeline and serving tooling such as MLflow, Kubeflow, SageMaker, Vertex, BentoML, or Feast
• Solid infrastructure skills in containers, Kubernetes, CI/CD, and at least one major cloud provider
• Data engineering capability to build reliable feature pipelines over operational, warehouse, and streaming data; understanding of training/serving skew
• Production experience monitoring models for drift, calibration, and tying model metrics back to business outcomes like fraud loss and approval rates
• Familiarity with fraud, risk, or credit modeling and explaining model behavior to non-ML stakeholders like banks and auditors
• Comfort working with AI-native tooling such as Claude Code as a daily driver, or genuine excitement to start
• A bias toward shipping; preference for a working v1 of a model pipeline today over a perfect platform next quarter

What we offer

• Base salary of $120,000-$180,000 USD plus equity

About Coinflow

Coinflow is a next-generation payment service provider founded in 2023, revolutionizing global financial infrastructure with stablecoins, AI-driven fraud prevention, and instant settlement. Since its seed round in 2024, Coinflow has achieved 23x revenue growth and scaled to multi-billion-dollar annual transaction volume. In October 2025, the company announced a $25M Series A led by Pantera Capital, CMT Digital, Coinbase Ventures, Jump Crypto, and Reciprocal Ventures.