Senior MLOps Engineer

Description: Architect, build, and maintain ML infrastructure on Google Cloud Platform (GCP). Collaborate with AI Researchers, Data Engineers, and Backend teams to deploy and monitor AI models in production. Requirements: At least 5 years of experience in MLOps and production ML workloads in cloud environments. Deep experience with GCP, including Vertex AI, GKE, and Cloud Storage. Expertise in containerization (Docker, Kubernetes) and model serving tools (Triton, MLflow). Proven experience with CI/CD tools (GitHub Actions, Airflow). Proficiency in Python and SQL for automation and data manipulation. Experience with ML observability tools (Grafana, Prometheus). Benefits: Opportunity to solve real customer problems in cybersecurity. Work in a nimble organization where individual contributions are valued. Accelerate your career in a fast-paced, growth-oriented environment.