Sr. Manchine Learning Engineer

Ria Money Transfer; Brasil; On-site; BRL 250,000 - 420,000; Full time

Benefits offered by this job

Annual Salary Increase

30 Days Vacation

Insurance Coverage

Job summary

Ria Money Transfer is seeking a Senior Machine Learning Engineer with a strong MLOps focus to own end-to-end ML pipelines in production. You will deploy, monitor, and scale real-time and batch workflows across cloud-based infrastructure and collaborate with data scientists, IT, and platform teams.

This role involves building CI/CD for ML, feature stores, model registries, and on-call weekend support when incidents occur. The candidate should have 5+ years of ML/DevOps experience.

Qualifications

• 5+ years in Machine Learning/ML engineering or related roles.
• Proficiency in Python and ML libraries.
• Experience with MLOps frameworks and tools.
• Strong containerization and deployment knowledge (Docker, Kubernetes).
• Proficiency with AWS and IaC tools (Terraform, CloudFormation).
• Experience with monitoring/observability stacks (Grafana, CloudWatch, Datadog).

Responsibilities

• Own real-time and batch ML pipelines from end to end.
• Build infrastructure for CI/CD, testing, deployment, and retraining of models.
• Implement feature stores, model registries, and orchestration for reproducible ML workflows.
• Deploy and serve models in low-latency production environments using containerized microservices.
• Set up monitoring for model performance, data quality, and operational health.
• Create automated alerts and dashboards for ML system visibility.
• Ensure model traceability, governance, and auditability.

Skills

Python

ML Libraries

MLOps Tools

Docker & Kubernetes

AWS & IaC

Monitoring & Observability

Tools

Terraform

CloudFormation

Grafana

Datadog

CloudWatch

Job description

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)

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 [e-mail].