PrincipalPlatformEngineer

Point Wild helps customers monitor, manage, and protect against the risks associated with their identities and personal information in a digital world. Backed by WndrCo, Warburg Pincus and General Catalyst, Point Wild is dedicated to creating the world’s most comprehensive portfolio of industry-leading cybersecurity solutions. Our vision is to become THE go-to resource for every cyber protection need individuals may face - today and in the future. Join us for the ride! We’re looking for a Principal Platform Engineer to architect and lead the infrastructure strategy for our next-generation Production ML platform on Google Cloud. In this role, you will be the backbone of our high-performance machine learning workloads, ensuring our systems are elastic, secure, and resilient. You won’t just maintain the status quo; you’ll build the "paved road" for our engineers, automating everything from model deployment to complex networking perimeters. We are a high-trust, outcome-focused team that moves quickly to solve some of the most challenging problems in the ML space. Core Responsibilities: Infrastructure Management: Design, deploy, and maintain elastic scaling cloud infrastructure (GCP) and containerization tools like Kubernetes for high-performance ML workloads. CI/CD Pipeline Development and maintenance: Build automated pipelines for training, testing, and deploying machine learning models using tools like Jenkins, GitHub Actions, or Airflow. Model Monitoring & Maintenance: Implement observability tools to track model drift, accuracy, latency, and performance degradation in production. Collaboration: Bridge the gap between data engineers, ML engineers, Backend and Frontend engineers to ensure smooth production operation. ML Observability: Implement comprehensive monitoring for system health (latency/uptime) alongside ML-specific metrics, such as feature drift, prediction accuracy, and data distribution shifts, to ensure long-term model reliability. Non ML workload and pro