Senior MLOps Engineer

We are seeking a Senior MLOps Engineer to build scalable machine learning infrastructure, model registries, and automated CI/CD for ML models. Tech stack: Python, Kubernetes, MLflow, CI/CD, Docker, Kubeflow, AWS, Feature Stores, Terraform What you will work on: - Design and maintain automated pipelines for model training, evaluation, registration, and deployment. - Implement automated monitoring solutions to detect data drift, model latency, and concept drift in production. - Operate containerized MLOps platforms on top of Kubernetes utilizing tools like MLflow, Kubeflow, and Argo. - Establish best practices for feature stores, dataset versioning, and secure model execution. What we are looking for: - Proven track record managing operational machine learning pipelines and MLOps platforms in production environments. - Strong skills in Python, Kubernetes, Docker, Terraform, and cloud infrastructure management. - In-depth understanding of both software engineering practices (CI/CD, automated testing) and machine learning workflows.