Grindr is seeking a Senior Staff MLOps Engineer to build and maintain ML infrastructure at scale for its AI-native platform. You will own the platforms for data ingestion, feature computation, model training, deployment, and monitoring, enabling ML teams to deliver recommendations, LLM experiences, ads, visual search, and trust & safety features.
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 engineers and data engineers to streamline workflows and enforce MLOps best practices.
Ensure reliability, scalability, and maintainability of ML systems.
Requirements
Bachelor's degree in CS, Engineering, Mathematics or related field.
5+ years experience in MLOps, ML platform engineering, or similar roles.
