MLOps Engineer
Pragmatic Play2 months ago
Remote, PortugalSenior
Responsibilities
- Design and operate scalable inference and serving systems for machine learning workloads.
- Design and maintain automated data, training, and inference pipelines.
- Build and manage CI/CD pipelines for application testing, validation, and deployment.
- Monitor and maintain deployed APIs for performance, reliability, and security.
- Create and manage internal platforms for configuring and managing ML systems in production.
- Develop observability dashboards and alerting systems for model and infrastructure health.
- Implement unit and integration tests for ML code, pipelines, and deployment workflows.
- Apply security best practices to containerized deployments and data handling.
Requirements
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
- Proficiency in Python with strong software architecture and development skills.
- Expertise in cloud platforms, preferably Azure, for scalable and reliable ML systems.
- Strong knowledge of version control systems, package management, and dependency tracking.
- Expertise in Docker-based containerization.
- Experience with monitoring, logging, and alerting for ML systems and infrastructure.
- Knowledge of general machine learning concepts and algorithms.
- Proven experience deploying and managing ML models in production environments.
- Knowledge of data modeling, ETL processes, and SQL and NoSQL database systems.