Senior Staff MLOps Engineer

Grindr is seeking a Senior Staff MLOps Engineer to build and own the infrastructure and tooling for ML pipelines at scale. This role involves architecting systems for data ingestion, feature computation, model training, deployment, and monitoring. The position is hybrid in Chicago or Bay Area offices.

• Build and maintain end-to-end ML pipelines for data ingestion, feature computation, model training, validation, deployment, and inference at substantial scale.
• Stand up and manage a feature store, ensuring feature consistency, lineage, and reuse across teams.
• Develop automated model deployment workflows with CI/CD, safe rollout strategies, and reproducibility guarantees.
• Implement monitoring and observability for ML systems including data quality checks, drift detection, and alerting.
• Build and support training environments with experiment tracking, distributed training, hyperparameter tuning, and artifact management.
• Collaborate with ML engineers and data engineers to streamline workflows and enforce MLOps best practices.

• Bachelor's degree in CS, Engineering, Mathematics, or related field.
• 5+ years experience in MLOps, ML platform engineering, or ML infrastructure.
• Strong experience building production ML pipelines and supporting end-to-end ML workflows.