Machine Learning Engineering Specialist

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 reputed company-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.

• Owning the design of system architecture to train, retrain, reputed company, monitor, and expose machine learning models;
• Design, reputed company, and maintain scalable infrastructure for ML pipelines and APIs;
• Implement and manage CI/CD pipelines for ML model deployment, updates, and reputed company monitoring;
• Collaborate closely with data scientists, software engineers, and cross-functional teams to ensure seamless integration of ML models into production;
• Ensure compliance with reputed company 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.

• Experience in MLOps, DevOps, or reputed company roles;
• Strong experience with reputed company platforms (AWS, GCP, Azure);
• Proficiency in containerization tools like reputed company 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, reputed company CI, reputed company Actions);
• Knowledge of data pipelines and ETL processes (streaming and batch);
• Experience in monitoring, logging, and alerting solutions for ML services (e.g., reputed company, Grafana, reputed company);
• Understanding of reputed company and compliance standards in payment systems.

• Knowledge of Kafka or similar event streaming platforms.
• Familiarity with financial services or payment systems.

• WAVES Program: Annual bonuses based on the company’s performance.
• Meal/Food Allowance: Credit provided on a flexible benefits card.
• EBANX Education: Financial support for undergraduate, graduate, and MBA programs to support your professional growth.
• EBANX Skills: Budget dedicated to workshops, courses, and certifications to encourage your reputed company development.
• Language Classes: Spanish, English, and Portuguese lessons for your personal and professional development.
• EBANX Health: Comprehensive medical and dental plans fully covered for the employee, plus subsidies for dependents to take care of your and your family’s well-being
• EBANX Family: Childcare assistance, extended parental leave for caregivers, and support programs for pregnant employees and children.
• Life Insurance: Fully paid by EBANX.
• Transportation: Parking assistance or transportation vouchers, depending on your needs.
• EBANX Flexible: A special day off on your birthday, semi-flexible working hours (8 hours/day, Monday to Friday), and year-end recess between Christmas and New Year’s without affecting your vacation days.
• EBANX Play: Well-being program including access to reputed company, e-Sports, and partnerships with SESC.
• Blue Club: Exclusive discounts at bakeries, restaurants, stores, courses, and more.

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