about 3 hours ago
Lisbon, PortugalEntry Level / Mid Level
Responsibilities
- Collaborate with ML Platform Engineers and Machine Learning Scientists to deliver scalable ML solutions.
- Deploy and operationalize ML models to production, bridging experimentation and real-world impact.
- Enhance and maintain the cloud-based ML Platform on GCP, writing production-grade Python and Terraform.
- Build and maintain CI/CD pipelines for ML model training and inference.
- Deploy, manage, and scale model serving endpoints on Kubernetes.
- Assist in developing and hosting custom and open-source AI tooling.
- Champion MLOps best practices around model versioning and automated retraining.
- Ensure platform reliability through observability, monitoring, and alerting.
Requirements
- 1+ year of experience deploying and maintaining ML models in production.
- Good understanding of MLOps principles, including experiment tracking and pipeline automation.
- Strong hands-on Python programming skills with proficiency in ML libraries.
- Familiarity with a major cloud platform, preferably GCP.
- Experience with containerization (Docker) and orchestration tools like Kubernetes.
- Strong context-switching ability with attention to detail.
- Preferably familiarity with infrastructure-as-code tools such as Terraform.
- Experience building and maintaining CI/CD pipelines for ML workflows.
Benefits
- Regular feedback and performance reviews to support development.
- Fair and transparent salary reviews.
- Opportunities for internal mobility and new projects.
- Support for personal growth and skill development.