Key Responsibilities:1.Design implement and maintain endtoend ML pipelines for model training evaluation and deployment2.Collaborate with data scientists and software engineers to operationalize ML models3.Develop and maintain CI/CD pipelines for ML workflows4.Implement monitoring and logging solutions for ML models5.Optimize ML infrastructure for performance scalability and costefficiency6.Ensure compliance with data privacy and security regulationsRequired Skills and Qualifications:1.Strong programming skills in Python with experience in ML frameworks2.Expertise in containerization technologies (Docker) and orchestration platforms (Kubernetes)3.Proficiency in cloud platform (AWS) and their MLspecific services4.Experience with MLOps tools5.Strong understanding of DevOps practices and tools (GitLab Artifactory Gitflow etc.6.Knowledge of data versioning and model versioning techniques7.Experience with monitoring and observability tools (Prometheus Grafana ELK stack)8.Knowledge of distributed training techniques9.Experience with ML model serving frameworks (TensorFlow Serving TorchServe)10.Understanding of MLspecific testing and validation techniques