Machine Learning Engineer - 5 at Adobe

The Challenge We are looking for a highly motivated individuals knowledgeable in ML Ops/ Platform engineering to be part of our Advertising Cloud Search, Social, Commerce, a leading digital marketing spend optimization platform helping enterprise clients achieving their marketing goals. We are now faced with exciting challenge of continuing the legacy and at the same time evolving and owning the digital marketing space through our innovative solutions. It's a robust agile team that collaborates and works across all functions of true product development. You must be that individual who is highly engaged, motivated and excels at critical thinking and problem solving! What you’ll do Model Lifecycle Management: Manage model versioning, deployment strategies, rollback mechanisms, and A/B testing frameworks. Coordinate model registries, artifacts, and promotion workflows in collaboration with ML Engineers Develop CI/CD and orchestration workflows using GitLab CI, GitHub Actions, CircleCI, Airflow, Argo Workflows, or similar tools. Review and optimize data science models, including code refactoring, containerization, deployment, versioning, and performance tuning. Implement model testing, validation, and automated QA pipelines, ensuring reproducibility and compliance. Monitor models in production, including data drift, concept drift, performance degradation, and system reliability. Collaborate multi-functionally with data scientists, data engineers, and architects; build documentation and improve team processes. Ensure governance, security, and compliance for ML pipelines (access controls, audit logs, model reproducibility, lineage). What you need to succeed Bachelor's degree or advanced degree or equivalent experience in Computer Science, Software Engineering or a related technical field. Strong ability to design and implement cloud architectures for end-to-end ML workflows on AWS. Hands-on experience with MLOps frameworks like MLflow, Kubeflow, Airflow or similar. Profic