At EBANX, a unicorn‑status fintech AI‑powered company, we need a Machine Learning Engineering Specialist to own design, deployment, and monitoring of scalable machine learning systems, collaborating with data scientists and software engineers.
Machine Learning Engineering Specialist at EBANX
More jobs at EBANXRequirements
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
- MLOps
- DevOps
- Cloud platforms
- Containerization
- Orchestration
- ML frameworks
- Python
- CI/CD
- Data pipelines
- ETL
- Monitoring
- Logging
- Alerting
- Security and compliance
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 ActionsPrometheusGrafanaDataDogKafkaETLData pipelinesStreamingBatch
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