Staff Machine Learning Ops Engineer

8+ years of experience with designing and building production-grade ML pipelines and systems – but don’t filter yourself out if you feel you’re a strong candidate with 5+ years. Strong knowledge of experiment tracking, model deployment strategies, data versioning, and monitoring. Experience with ML infrastructure tools (e.g. MLflow, Kubeflow, Airflow, feature stores, model registries). Familiarity with GCP and VertexAI preferred, but not required. Strong communication skills and ability to align technical solutions with business goals. Comfortable making architectural decisions and balancing best practices with practical trade-offs.

design, build, and maintain automated pipelines for training, testing, and deploying ML models design, build, and maintain experiment tracking systems for performance metrics, data and model versioning, and documentation design, build, and maintain processes and systems for the full model lifecycle, including registries, release and rollback strategies, and scalable model serving design, build, and maintain monitoring and alerting for prediction quality, system health, and cost optimization influence the direction of data and ML within Overstory by: advocating for a balance between MLOps best practices and quick slices of value; aligning technical solutions with customer needs in collaborating with both engineering and product; ensuring our MLOps systems support regulatory, privacy, and security requirements