Grindr is seeking a Senior Staff MLOps Engineer to build and own the infrastructure for AI systems. This role involves designing end-to-end ML pipelines, managing feature stores, and implementing monitoring for recommendations, LLM experiences, and trust & safety. The candidate will work with a lean, high-impact team in a hybrid role (Bay Area or Chicago).
Responsibilities
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, performance metrics, and alerting.
Build and support training environments with experiment tracking, distributed training, hyperparameter tuning, and artifact management.
Collaborate with ML and data engineers to streamline workflows and enforce MLOps best practices.
Requirements
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 workflows.
