Oversee and manage the build and maintenance of robust and scalable ML pipelines; Design and implement automated workflows for data ingestion, model training, deployment, monitoring, and governance; Collaborate with data scientists and engineers to ensure seamless integration of ML models into production environments using Kubernetes service; Develop and implement best practices for ML platform security, reliability, and performance; Monitor and assess model performance and implement corrective actions
Requirements:
5+ years of experience in ML Ops or a related field; Proven track record of building and managing ML pipelines, including data preparation, model training, deployment, and monitoring; Solid foundation in DevOps principles and practices with experience in CI/CD pipelines for ML deployments; Solid programming skills Python or other scripting language
Text:
ML Ops Engineer/Lead Oversee and manage the build and maintenance of robust and scalable ML pipelines; Design and implement automated workflows for data ingestion, model training, deployment, monitoring, and governance; Collaborate with data scientists and engineers to ensure seamless integration of ML models into production environments using Kubernetes service; Develop and implement best practices for ML platform security, reliability, and performance; Monitor and assess model performance and implement corrective actions 5+ years of experience in ML Ops or a related field; Proven track record of building and managing ML pipelines, including data preparation, model training, deployment, and monitoring; Solid foundation in DevOps principles and practices with experience in CI/CD pipelines for ML deployments; Solid programming skills Python or other scripting language
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