Machine Learning Engineering Specialist

At EBANX, we believe barriers were made to be broken. We started our story in Curitiba, Brazil, and today we are a global company, present in more than 29 countries, with offices in Curitiba, São Paulo, Shanghai, Singapore, and Johannesburg. In total, we are 700+ ebankers spread across the world, connecting companies like Uber, Netflix, Spotify, TikTok, Canva, Shopee, Meta, and Shein to millions of consumers in emerging markets—creating new opportunities and revolutionizing the future of digital payments.

Our mission is clear: to give global access to everyone. We are guided by the motto #TamoJunto, which translates into four key pillars: Shape Tomorrow, Evolve Fast, Make It Happen, and Unlock The World.

If you want to be part of a global company with accelerated growth that is shaping the future of digital payments, EBANX is the place for you.

At EBANX’s Data team you don’t just work with numbers. You transform information into intelligence that drives strategic decisions and directly impacts the digital payments revolution on a global scale. Every analysis combines curiosity, rigor, and collaboration, making our work truly Out of the Ordinary.

What your day-to-day will look like

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

What you need to shine in this role

• Experience in MLOps, DevOps, or related roles;
• Strong experience with cloud platforms (AWS, GCP, Azure);
• Proficiency with containerization tools such as Docker and orchestration systems (e.g., Kubernetes);
• Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn);
• Strong Python skills with experience 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 with monitoring, logging, and alerting solutions for machine learning services (e.g., Prometheus, Grafana, Datadog);
• Understanding of security and compliance standards in payment systems.

Bonus points if you have

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

EBANX offers:

• Performance Bonus: Annual bonus program based on company results.
• Meal Allowance: Monthly allowance to support your meals.
• EBANX Education: Financial assistance for undergraduate, graduate, and MBA programs to support your professional growth.
• EBANX Skills: Dedicated budget for courses, certifications, and workshops to encourage continuous learning.
• Language Classes: Language classes to support your personal and professional development.
• Health & Well-being: Medical and dental plans with extensive coverage, including support for dependents and wellness programs.
  Flexible Work Culture: Semi-flexible hours, additional day off on your birthday, and year-end break to support work-life balance.
• Well-being Program: Access to activities and resources that promote physical and mental health.

Learn more about our #ebanxlife on LinkedIn and Instagram, and see what it’s like to be part of a global team that breaks barriers, creates opportunities, and celebrates every achievement together.

✨ An Out Of The Ordinary career is waiting for you here!