Senior ML Software Engineer

Global Payments; Greater London; On-site; GBP 90,000 - 140,000; Full time

Job summary

Global Payments is seeking a Senior ML Software Engineer to build and operate production ML-backed services. You will own backend features, APIs, and platform tooling, delivering high-velocity, reliable ML-powered solutions in a cross-functional team.

You will focus on production engineering, CI/CD, monitoring, and incident response while collaborating with ML researchers and product managers to ship scalable ML capabilities at pace.

Qualifications

• 5+ years as a software engineer with production backend/MLops experience.
• Experience deploying ML models as production services and managing endpoints.
• Strong Python and backend service development skills.

Responsibilities

• Design, implement, and deploy production ML services and APIs.
• Own end-to-end reliability and performance (SLO-driven) of ML systems.
• Mentor teammates and drive collaboration with ML researchers and product teams.

Skills

Python

API design

Kubernetes

Docker

Terraform

CI/CD

Monitoring

On-call

FastAPI/OpenAPI

Flask

Go

Java

DynamoDB

MLFlow

SageMaker Pipelines

Databricks

PCI/HIPAA/SOC2

Tools

Kubernetes (EKS/OpenShift)

Docker

Terraform

Job description

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 ownSoftware 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 bring5+ years as an software engineer, MLOps Engineer, or similar, with hands-on production experience operating backend services or ML-backed APIsProven expertise deploying ML models as production services, API design, and service integrationStrong 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 responseExperience monitoring, troubleshooting, optimizing production ML systems (latency, throughput, availability)Excellent communication and cross-functional collaboration skillsDemonstrated ability to work independently, navigate ambiguity, resolve blockers, and deliver results with a strong sense of urgencyIt’s a bonus if you haveExperience with MLFlow / model versioning, SageMaker Pipelines, or DatabricksFamiliarity with real-time, high-volume data products and low-latency data stores (e.g. DynamoDB)Automated testing and validation frameworks for models and servicesExperience in regulated industries (e.g. PCI, HIPAA, SOC2), large companies, or mature engineering teamsOptional familiarity with LLM tooling / RAGWhy Join Us?Impact: Own high-profile ML-backed services that power customer-facing products driving measurable business outcomesAutonomy: Take end-to-end technical ownership of your product area, with the responsibility and freedom to drive robust technical solutions, shape best practices, and deliver results in a fast-paced, supportive environment.Collaboration: Join a cross-functional, high-performing team where your expertise is valued and grow with industry experts across engineering and product.About the teamOur inclusive and global teams win together every day. We’re proud to have the best minds in the industry, whom you can learn from as you grow your career. The people, the energy, and the connections are unmatched. Come and be part of an ever-evolving company and get dynamic opportunities that transcend borders.What makes a Globalpayer?Globalpayers think like a client, act like an owner, and win as one team. We’re curious and innovative – always finding better ways to deliver impact. We empower each other to make decisions, and our passion drives excellence in everything we set out to do.Does this sound like you? Then you sound like a Globalpayer. Apply now to take your career global.#LI-AB1