Associate MLOps Engineer

Role Overview

Support the deployment, scaling, optimization, and monitoring of AI/ML models in production environments. Work closely with data scientists and developers to ensure models run efficiently, reliably, and with fast inference performance.

Key Responsibilities

• Develop, maintain, and deploy ML/AI models into production environments.
• Build and serve model inference APIs using frameworks like FastAPI.
• Optimize models for better inference performance including quantization and model compression.
• Package and containerize models using Docker and manage deployments with orchestration tools (e.g., Kubernetes).
• Set up CI/CD pipelines and automation workflows for model deployment.
• Monitor model performance, latency, and reliability in production.
• Troubleshoot and resolve deployment, infrastructure, or inference issues.
• Collaborate with ML Engineers, Data Scientists, and DevOps ...