AI Expert in Machine Learning Engineering

1 semana atrás

Brasil beBeeMLOPS Tempo inteiro R$1.000.000 - R$1.500.000
Transforming Payments with AI

At our company, you'll be part of a dynamic team that's revolutionizing access to payments and technology in emerging markets. With our AI-powered platform, we're scaling fast across 29 countries, connecting leading global companies to over 1 billion consumers.

We build innovative solutions that are both efficient and inclusive. Our data scientists are naturally curious, driven by evidence, and passionate about turning information into intelligence.

As an MLOps specialist, your mission will be to design, deploy, and maintain scalable systems for training, monitoring, and exposing machine learning models in production.

Key Responsibilities:
  • Design system architecture to train, retrain, develop, monitor, and expose machine learning models.
  • 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.
  • Troubleshoot and optimize ML production systems for 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:
  • Experience in MLOps, DevOps, or related roles.
  • Strong experience with cloud platforms.
  • 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).

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