Machine Learning Engineering Specialist na EBANX

Remoto - Remote in Brazil

At EBANX, you’ll help expand access to payments and technology in some of the world’s most dynamic markets. We’re a unicorn‑status fintech, AI‑powered, and scaling fast across 29 countries and counting.

Our platform connects leading global companies to more than 1 billion consumers, enabling seamless cross‑border payments where it matters most. We build with purpose, move with speed, and create solutions that are both innovative and inclusive.

If you’re looking to be part of a company that’s transforming the future of payments with clarity, ambition, and real‑world impact — we’d love to meet you.

In the Data team, we turn information into intelligence. We model, organize, and analyze data to generate strategic insights that drive decision‑making across EBANX. We're naturally curious and guided by evidence. As a Data Scientist Specialist focused on MLOPs your mission will be to own the design and deployment of scalable systems to train, monitor, and expose machine learning models in production.

Requirements

Experience

Experience in MLOps, DevOps, or related roles
Strong experience with cloud platforms (AWS, GCP, Azure)
Proficiency in containerization tools like Docker and orchestration systems (e.g., Kubernetes)
Familiarity with ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn)
Strong Python skills with experience in writing clean, efficient, and maintainable code
Experience with CI/CD tools (e.g., Jenkins, GitLab CI, GitHub Actions)
Knowledge of data pipelines and ETL processes (streaming and batch)
Experience in monitoring, logging, and alerting solutions for ML services (e.g., Prometheus, Grafana, DataDog)
Understanding of security and compliance standards in payment systems

Skills

Experience in MLOps, DevOps, or related roles
Strong experience with cloud platforms (AWS, GCP, Azure)
Proficiency in containerization tools like Docker and orchestration systems (e.g., Kubernetes)
Familiarity with ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn)
Strong Python skills with experience in writing clean, efficient, and maintainable code
Experience with CI/CD tools (e.g., Jenkins, GitLab CI, GitHub Actions)
Knowledge of data pipelines and ETL processes (streaming and batch)
Experience in monitoring, logging, and alerting solutions for ML services (e.g., Prometheus, Grafana, DataDog)
Understanding of security and compliance standards in payment systems

Responsibilities

Owning the design of system architecture to train, retrain, develop, monitor, and expose machine learning models
Design, develop, and maintain scalable infrastructure for ML pipelines and APIs
Implement and manage CI/CD pipelines for ML model deployment, updates, and continuous monitoring
Collaborate closely with data scientists, software engineers, and cross-functional teams to ensure seamless integration of ML models into production
Ensure compliance with security and privacy requirements, particularly in a financial context
Troubleshoot and optimize ML production systems, ensuring performance, reliability, and scalability
Share knowledge, mentor, and support team members in best practices for MLOps, API development, and productionization of machine learning models

Technologies

AWSGCPAzureDockerKubernetesTensorFlowPyTorchScikit-learnPythonJenkinsGitLab CIGitHub ActionsPrometheusGrafanaDataDogKafka

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