Principal MLOps / Platform Engineer

Principal MLOps / Platform Engineer

Poland, Remote or Ukraine, Remote or Romania, Remote

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 MLOps / 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 production metrics monitoring.

• Deploy tools that empower individual teams to monitor their workloads.

• Participate in on-call rotation, help manage posture to ensure compliance with standards such as SOC.

What you bring to the table:

• Senior Expertise: 8 - 10+ years in DevOps/Platform Engineering, with at least 2 years of experience specifically operating and maintaining production ML workloads.

• GCP & K8s Mastery: Deep, hands-on experience with GCP (VPC-SC, IAM, Organization Policies) and GKE (Cluster topology, Helm, Kustomize, and in-cluster operators like ArgoCD).

• Service Mesh Excellence: High proficiency with Istio (VirtualServices, mTLS, sidecar injection) and API Gateways (specifically Kong).

• Infrastructure as Code: Expert-level Terraform skills, specifically using an Atlantis/GitOps workflow across a massive, multi-hundred-file estate.

• Secrets & Identity: Experience managing enterprise-grade identity and secrets (Auth0, Dex, ESO, or SOPS).

• Data/ML Tooling: Experience operating Airflow in production and an ML-serving stack (e.g., Triton, vLLM, MLflow).

• Database Management: Comfortable managing Cloud SQL (PostgreSQL), BigQuery, and in-cluster datastores like Elasticsearch or ClickHouse.

• At least an upper-intermediate level of spoken and written English.

It would be great if you also had:

• ML Observability: Past experience with continuous monitoring of model accuracy and detecting data/concept drift.

• Automation Savvy: Experience with Ansible for cluster bootstrap and recovery.

• Advanced Certifications: Kubernetes (CKA/CKS) or GCP Professional Cloud Architect/Security Engineer certifications.

• Modern Stack Exposure: Familiarity with Loki, Grafana, or managing ClickHouse at scale.

Why Join Us?

• Professional Growth: Enhance your skills by collaborating closely with talented engineers and architects.

• Meaningful Impact: Help create software that protects millions of users from cybersecurity threats.

• Supportive Environment: Join a team dedicated to innovation, mentorship, and continuous learning.