Senior MLOps Engineer

📋 Description Architect and manage scalable GCP-based ML infrastructure using Vertex AI, GKE, GCS, Cloud Run, and Own the end-to-end deployment lifecycle for machine learning models; build high-throughput Build automated, reproducible pipelines for model training, testing, evaluation, and deployment Implement robust monitoring systems for system health (latency, throughput, uptime) and ML-specific Provide scalable training environments, optimized runtime infrastructure, and standardized Collaborate with Data Engineers to integrate model pipelines with feature stores, dataset 🎯 Requirements At least 5 years of hands-on experience designing, deploying, and maintaining production ML Deep practical experience with Google Cloud Platform (GCP), including Vertex AI, Cloud Storage Expertise with containerization (Docker, Kubernetes/GKE) and specialized serving tools (Triton Proven track record with workflow orchestrators (Airflow, Vertex AI Pipelines) and modern CI/CD Solid experience managing cloud resources using Terraform. Proficiency in Python and SQL for scripting, automation, API development, and data manipulation. 🎁 Benefits Solve real customer problems See your impact Accelerate your career Work with other talented people at a company where people matter