Senior ML Software Engineer

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, availability)
• Excellent communication and cross-functional collaboration skills
• Demonstrated ability to work independently, navigate ambiguity, resolve blockers, and deliver results with a strong sense of urgency

It’s a bonus if you have

• Experience with MLFlow / model versioning, SageMaker Pipelines, or Databricks
• Familiarity with real-time, high-volume data products and low-latency data stores (e.g. DynamoDB)
• Automated testing and validation frameworks for models and services
• Experience in regulated industries (e.g. PCI, HIPAA, SOC2), large companies, or mature engineering teams
• Optional familiarity with LLM tooling / RAG

Why Join Us?

• Impact: Own high-profile ML-backed services that power customer-facing products driving measurable business outcomes

• Autonomy: 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 team

Our 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.

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