MLOPS with AWS Sagemaker, Terraform

We are seeking a skilled MLOps Engineer to streamline and automate the deployment, monitoring, and management of machine learning models in production environments. The ideal candidate will have experience in both machine learning and DevOps practices to ensure scalable, reliable, and efficient ML solutions. Responsibilities: Develop, implement, and maintain ML pipelines for model deployment and management Collaborate with data scientists to convert prototypes into production-ready solutions Automate CI/CD processes for ML models using tools like Jenkins, GitLab, or CircleCI Monitor model performance and ensure reliability and scalability in production Manage cloud infrastructure (AWS, GCP, Azure) for ML workloads Implement data versioning, model versioning, and experiment tracking Troubleshoot and resolve deployment issues Ensure security and compliance standards are met Qualifications: Bachelor’s or Master’s degree in Computer Science, Data Science, or related field Proven experience in MLOps, DevOps, or related roles Strong knowledge of ML frameworks (TensorFlow, PyTorch, scikit-learn) Experience with cloud platforms (AWS, GCP, Azure) Familiarity with containerization (Docker, Kubernetes) Proficiency in scripting languages like Python or Bash Understanding of CI/CD pipelines and automation tools Excellent problem-solving and communication skills