Senior Staff MLOps Engineer

Description du poste

As a Staff MLOps Engineer, you will build and own the infrastructure, tooling, and scalable systems that make high-impact AI possible You’ll architect and maintain the platforms that power data ingestion, feature computation, model training, automated evaluation, deployment, and ongoing monitoring for the ML teams building recommendations, LLM-based experiences, ads, visual search, growth, and trust & safety You will design foundational systems that allow our ML engineers to experiment faster, ship models more reliably, and operate them with confidence in production We’re looking for an exceptional MLOps engineer who’s passionate about enabling ML at scale, (>6M daily active users and 100’s of millions of daily user interactions) Someone who loves building robust, automated pipelines; creating reliable production training and inference systems; and establishing the infrastructure and processes that accelerate ML product development across the organization In this role, you will shape and execute the strategy for Grindr’s ML platform and end-to-end model lifecycle Build and maintain end-to-end ML pipelines for data ingestion, feature computation, model training, validation, deployment, and inference, all at substantial scale of data Stand up and manage a feature store, ensuring feature consistency, lineage, and reuse across teams Expertise with best in class tools for managing deployment, scheduling, and environments and how to use them in the specialized regime of ML Infrastructure 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 and environment management Collaborate with ML engineers and data engineers to streamline workflows, improv

Annonce publiée sur Welcome to the Jungle et reprise par Intelligence Academy. Seule l'annonce d'origine fait foi ; nous ne sommes pas l'employeur.