Responsibilities
- Build and maintain ML pipelines for training, evaluation, and deployment.
- Create reproducible, containerized model-training environments and manage large-scale compute, including GPU and spot autoscaling.
- Define observability and alerting for ML systems, including model drift, data quality, and feature coverage.
- Design and scale batch and streaming data-ingestion and feature-transformation flows.
- Develop internal Python libraries and platform tooling that accelerate ML experimentation and deployment.
- Ensure ML services are modular, testable, and monitored from the start.
- Explore and productionize LLM-based features, including retrieval pipelines, prompt evaluation, and model serving.
- Collaborate with ML Scientists, Backend Engineers, and Data Engineers, and mentor peers in reliability, testing, and delivery.

Requirements
- 5+ years of relevant experience designing and deploying production ML systems.
- Proficiency in Python, SQL, and workflow orchestration tools such as Airflow, Kubeflow, or Dagster.
- Experience with modern cloud platforms,



preferably GCP or AWS, as well as Kubernetes and CI/CD workflows.
- Understanding of the ML lifecycle, including training, validation, deployment, and monitoring.
- Strong DevOps practices involving Git, Terraform, logging and observability, Docker, and Kubernetes.
- Ability to work independently with ML Scientists and mentor peers.
- Exposure to LLM serving, vector databases, or generative-AI product flows.
- Deep hands-on expertise with AI tools, especially agentic AI software development life cycle practices.

Benefits
- Open, collaborative, dynamic, and diverse workplace culture.
- Monthly allowance for lessons on Preply.com.
- Learning and Development budget and time off for self-development.
- Competitive financial package with equity, leave allowance, and health insurance.
- Access to free mental health support platforms.
- Opportunity to contribute to language learning and teaching produ

📌 Senior Machine Learning Platform Ops (España)
🏢 Preply
📍 España