MLOps Engineer

Job description

Overview/ Job Responsibilities Job Summary: We are seeking a skilled MLOps Engineer to join our team and ensure the seamless deployment, monitoring, and optimization of AI models in production. The MLOps Engineer will design, implement, and maintain end-to-end machine learning pipelines, focusing on automating model deployment, monitoring model health, detecting data drift, and managing AI-related logging. This role will involve building scalable infrastructure and dashboards for real-time and historical insights, ensuring models are secure, performant, and aligned with business needs. Key Responsibilities: - Model Deployment : Deploy and manage machine learning models in production using tools like MLflow, Kubeflow, or AWS SageMaker, ensuring scalability and low latency. - Monitoring and Observability : Build and maintain dashboards using Grafana, Prometheus, or Kibana to track real-time model health (e.g., accuracy, latency) and historical trends. - Data Drift Detection : Implement drift detection pipelines using tools like Evidently AI or Alibi Detect to identify shifts in data distributions and trigger alerts or retraining. - Logging and Tracing : Set up centralized logging wit...