Platform Engineer

• Collaborate closely with ML Platform Engineers, Machine Learning Scientists, and engineers across Mollie's domain teams to deliver scalable Machine Learning solutions
• Deploy and operationalize ML models to production in partnership with Machine Learning Scientists, bridging the gap between experimentation and real-world impact
• Enhance and maintain our cloud-based ML Platform on GCP, writing production-grade Python and Terraform daily
• Build and maintain CI/CD pipelines for ML model training and inference, ensuring reliable and automated workflows across environments
• Deploy, manage, and scale model serving endpoints on Kubernetes, ensuring low-latency, high-availability inference for production workloads
• Assist in extending, developing, and hosting custom and open-source AI tooling; enabling teams to rapidly build and deploy AI-powered solutions
• Champion MLOps best practices, implementing standards around model versioning, experiment tracking, data validation, and automated retraining
• Ensure platform reliability by setting up observability, monitoring, and alerting for both infrastructure and deployed models
• Maintain and enhance open-source AI tooling hosted at Mollie (such as LiteLLM and LibreChat), and further support and expand our generative AI capabilities.

Machine Learning Platform Engineer I

• Develop, implement and optimize data pipelines using Spark and Spark Streaming
• Write scalable, object-oriented Python code following best practices (PEP 8), with unit and integration tests
• Work with SQL for data modeling, query optimization and integration with analytical systems
• Use Databricks for managing clusters, notebooks and Delta Lake
• Collaborate with technical and non-technical teams, facilitating communication and understanding of requirements
• Implement DevOps practices and deployment automation using GitHub and GitHub Actions
• Ensure code quality and work in Agile environments

Data Platform Engineer, Mid

• Design and implement secure, scalable AWS infrastructure solutions using tools such as Terraform and CloudFormation
• Refactor organization-wide environments, standardizing multi-account landing zones, unified IAM models, and automated compliance guardrails aligned with CIS benchmarks
• Standardize core cloud networking, including DNS management, traffic segmentation, routing patterns, and secure cross-cloud/intra-cloud connectivity
• Manage containerized applications using Docker and Kubernetes/EKS, ensuring optimal performance, scalability, and zero-trust network policies
• Develop and optimize end-to-end deployment pipelines (GitHub Actions, GitLab CI, Jenkins) and create custom automation scripts using Python, Bash, or Go
• Implement and maintain robust logging, monitoring, and alerting systems (CloudWatch, Prometheus, VictoriaMetrics, ELK) to enhance operational readiness and reduce downtime

AWS Platform Engineer

• Design, build, and maintain scalable data pipelines using AWS Glue (PySpark)
• Engineer and optimise the ClickHouse warehouse for sub-second query performance
• Implement data contracts between back-office and the platform
• Build the feature-serving layer providing pre-computed features to AI agents
• Integrate with third-party databases and external systems
• Establish monitoring, alerting, and maintenance procedures
• Own CI/CD and infrastructure-as-code for data workloads
• Collaborate with data scientists and engineering teams

Platform Engineer jobs in Portugal

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Machine Learning Platform Engineer I

Data Platform Engineer, Mid

AWS Platform Engineer

Data Platform Engineer