MLOps Lead

About the Role We are looking for an experienced MLOps Lead to define and drive the machine learning infrastructure strategy for our platform. This is a hands-on leadership role focused on building scalable, reliable, and production-ready ML systems while mentoring a growing MLOps team. Key Responsibilities Define the MLOps architecture and platform strategy Design scalable pipelines for training, deployment, and monitoring of ML models Lead deployment and management of ML workloads on cloud platforms (GCP / AWS) Ensure reliability, scalability, and performance of ML systems Define best practices for model versioning, monitoring, and lifecycle management Collaborate with data science, DevOps, and backend teams Improve automation, reproducibility, and production readiness of ML systems Mentor and guide MLOps engineers What We’re Looking For 8+ years of experience in DevOps / ML Engineering / MLOps Strong hands-on experience with Python Deep knowledge of cloud platforms (GCP preferred / AWS acceptable) Strong experience with Docker, Kubernetes, and ML model deployment Experience designing production ML pipelines Experience with MLflow, Kubeflow, Vertex AI, or SageMaker Strong understanding of distributed systems and scalable infrastructure Experience working in SaaS or product-based environments Strong technical leadership experience Nice to Have Experience managing GPU-based environments Experience with large-scale ML pipelines Knowledge of data engineering tools