Responsibilities:
Implement and manage pipelines for deploying AI/ML models to production.
Optimize models for performance, scalability, and resource efficiency.
Monitor deployed models for accuracy, latency, and overall performance.
Collaborate with data scientists and engineers to ensure seamless integration.
Troubleshoot deployment issues and maintain deployment infrastructure.
Requirements:
Strong experience with containerization tools (Docker, Kubernetes).
Proficiency in Python and familiarity with AI frameworks (e.g., TensorFlow, PyTorch).
Experience with cloud platforms (AWS, Azure, or Google Cloud) for AI deployment.
Knowledge of CI/CD pipelines and MLOps practices.
Bachelor’s or Master’s in Computer Science, AI, or related field.