Senior MLOps Engineer

Point Wild is a cybersecurity company dedicated to creating comprehensive solutions for identity protection and risk management. We are looking for a Senior MLOps Engineer to join our team and help us bridge the gap between AI experimentation and high-performance, enterprise-grade production systems.

Key responsibilities

• Architect and manage scalable GCP-based ML infrastructure using Vertex AI, GKE, and Cloud Run.
• Own the end-to-end deployment lifecycle for machine learning models, ensuring high-throughput and low-latency inference.
• Build automated, reproducible pipelines for model training, testing, and deployment using Airflow and Vertex AI Pipelines.
• Implement robust monitoring systems for both system health and ML-specific metrics like feature drift and prediction accuracy.
• Collaborate with AI researchers and data engineers to transition prototypes into resilient, auto-scaling microservices.

Requirements

• At least 5 years of hands-on experience designing and maintaining production ML workloads in cloud environments.
• Deep practical experience with the GCP ecosystem, including Vertex AI, GKE, and IAM configurations.
• Expertise in containerization and specialized serving tools such as Triton, vLLM, or MLflow.
• Proven track record with workflow orchestrators and modern CI/CD tools like GitHub Actions or ArgoCD.
• Solid experience managing cloud resources using Terraform and proficiency in Python and SQL.

What we offer

• The opportunity to operationalize AI models that create real-world value at scale.
• A role that serves as the infrastructure backbone, empowering AI teams to innovate rapidly.
• A cross-functional environment where you connect data science, cloud operations, and software engineering.