Sr Machine learning Engineer

Description

Ria Money Transfer, a business segment of Euronet Worldwide, Inc. (NASDAQ: EEFT), delivers innovative financial services including fast, secure, and affordable global money transfers to millions of customers along with currency exchange, mobile top-up, bill payment and check cashing services, offering a reliable omnichannel experience. With over 600,000 locations in nearly 200 countries and territories, our purpose remains to open ways for a better everyday life.

We believe we can create a world in which people are empowered to build the life they dream of, no matter who they are or where they are. One customer, one family, one community at a time.

ABOUT THIS ROLE

We're looking for a Sr Machine Learning engineer with a strong focus on MLOps to join our growing team. In this role, you'll own the end-to-end infrastructure and automation of ML pipelines, with a focus on deploying, scaling, monitoring, and maintaining real-time and batch machine learning workflows in production environments.

This role collaborates closely with data scientists, IT, and platform teams to ensure ML models are production-ready, reliable, and observable at scale.

ROLES & RESPONSIBILITIES

• Own, design, build, and maintain real-time and batch ML and pipelines supporting the end-to-end ML lifecycle.
• Develop infrastructure and tooling for continuous integration, testing, deployment, and retraining of ML models.
• Implement and operate feature stores, model registries, and orchestration frameworks for reproducible ML workflows.
• Deploy and serve ML models in low-latency and high-throughput production environments using containerized microservices.
• Implement robust monitoring systems for Model Performance, Data quality, and Operational health.
• Build automated alerting and dashboarding for visibility into ML system health.
• Ensure model traceability, auditability, and governance practices.
• Optimize infrastructure on cloud platforms (AWS) using Infrastructure as Code.
• As part of our ML operation team, this role will be responsible to occasionally be on call over the weekends in the events of incidents.

POSITION REQUIREMENTS

• 5+ years of experience as a Machine Learning Engineer, MLOps Engineer, or related role.
• Proficiency in Python and ML libraries (e.g., scikit-learn,…)
• Experience with MLOps frameworks and tools
• Strong understanding of containerization and deployment (Docker, Kubernetes).
• Proficiency with AWS and IaC tools (Terraform, CloudFormation).
• Experience with monitoring and observability stacks ( Grafana, CloudWatch, Opsgenie, Datadog).
• Familiarity with streaming and batch data systems ( Spark, PySpark, Kenises).
• Excellent problem-solving and communication skills; comfortable working cross-functionally.

PERKS & BENEFITS

• Annual Salary Increase Review
• 30 Days of Vacation Per Year
• Comprehensive Insurance Coverage ( Health, Oncological, Dental, and Life Insurance)
• Meal Allowance
• English Course Subsidy/Language Assistance
Growth Opportunities

Ria Money Transfer is an Equal Employment Opportunity employer. All qualified applicants will be considered for employment regardless of age, national origin, race, color, disability, religion, sexual orientation, gender identity or expression, or any other characteristic protected under applicable law. We celebrate diversity and are committed to creating an inclusive environment for all employees. We are committed to providing reasonable accommodations to qualified individuals with disabilities. If you need assistance or an accommodation due to a disability, you may contact us at [email protected].

Check out our website to learn more about the company at: http://www.riamoneytransfer.com/

The position responsibilities outlined above are intended to define the general contents and requirements to perform this job. It is not to be taken as a complete statement of responsibilities or requirements. This job description does not restrict the Company's right to assign or reassign duties and responsibilities to this job as needed.

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