Senior ML Software Engineer

Ready to take your career global? Make your mark at one of the biggest names in payments. We are seeking an experienced Senior ML Software Engineer to join our ML team, with a strong focus on payment optimization. You will be the primary software engineering expert for a product area, working as part of a cross-functional agile team and owning the successful launches and ongoing operations of high-profile products in production. This is a senior software engineering / MLOps role focused on building and operating production services and platform capabilities, not a model research role. Data science experience is valuable but secondary to production engineering and operational ownership. Your focus will be on driving new feature delivery, maintaining operational excellence, and collaborating on enhancements to our shared ML platform. In addition to technical expertise, this job requires strong collaboration skills. You will work closely with cross-functional collaborators—including ML research engineers, product managers, and platform engineers—to deliver scalable, reliable, and low-latency ML solutions. What you’ll own Software and Service Delivery: Design, implement, and deploy software features, backend services, and APIs that operationalize ML models in production (with a focus on backend, API, and service work, rather than model research). Technical Ownership and Stewardship: Full technical ownership of existing and new production ML services in your area, ensuring alignment of technical investments with business goals and engineering best practices. End-to-end stewardship of service reliability and performance (SLO-driven). Contribute to the ML platform: Evolve shared platform tooling and standards to improve developer velocity, reliability, and repeatable delivery across teams. Operational Excellence: Maintain and improve automated CI/CD pipelines, testing frameworks, and monitoring/logging; own pre-release testing, rollouts, and release coordination. Participate in on-call rotations and lead incident response, root cause analysis, and remediation for your product area. Leadership: Provide technical guidance to engineers and data scientists, mentor teammates, and drive continuous improvement and knowledge sharing.   What you’ll bring 5+ years as an software engineer, MLOps Engineer, or similar, with hands-on production experience operating backend services or ML-backed APIs Proven expertise deploying ML models as production services, API design, and service integration Strong Python skills and service/backend engineering experience (ideally in FastAPI/OpenAPI, Flask, Go, or Java) Production experience with containerization and orchestration (ideally Kubernetes – EKS/OpenShift), Docker, and IaC (ideally Terraform or Terraform Cloud) Ownership of CI/CD pipelines, monitoring/alerting, and on-call/incident response Experience monitoring, troubleshooting, optimizing production ML systems (latency, throughput,…