Intelligent Systems Developer

Há 4 dias

Curitiba, Paraná, Brasil beBeeMachineLearning Tempo inteiro R$900.000 - R$1.500.000

We're driving innovation in cross-border payments and technology. Our platform connects global companies to over 1 billion consumers, enabling seamless transactions in dynamic markets.

Role Overview

We build with purpose and speed, creating solutions that are both innovative and inclusive. In the Data team, we turn information into actionable insights that drive strategic decision-making.

This role will focus on designing and deploying scalable systems to train, monitor, and expose machine learning models in production.

Main Responsibilities:
  • Design and develop system architecture for training, retraining, developing, monitoring, and exposing machine learning models;
  • Create 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.
Requirements and Qualifications:
  • Experience in MLOps, DevOps, or related fields;
  • 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 our industry.

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