AI Data and MLOps Engineer

2 months ago


chennai, India SGK Full time

About SGKSGK is a global packaging and brand experience company. From idea to implementation, we deliver packaging solutions and brand experiences that give brands the freedom to speak louder, scale faster and grow stronger. We simplify marketing and amplify brands to deliver value. SGK is a Matthews International company.Position SummarySGK seeks an AI Data and MLOps Engineer to join our Production IT team and AI Lab. Directed by the Director of Digital Content Strategic Solutions A.I. & Cloud Governance, you'll work on innovative projects at the intersection of AI, Data Science, MLOps, and Cloud technologies. You'll design, develop, and maintain data pipelines and infrastructure to support AI-powered solutions on AWS Cloud environments. Your role will involve implementing MLOps practices, automating model deployment, and setting up monitoring systems to ensure seamless integration and performance of AI models and applications.Key ResponsibilitiesDesign and implement scalable data pipelines on AWS for ingesting, transforming, and storing large volumes of dataDevelop data warehouses, data lakes, and other storage solutions on AWS, ensuring data quality, security, and accessibilityCollaborate with AI developers and data scientists to understand and meet data requirements for AI modelsImplement data governance and management best practices, ensuring compliance with privacy and security regulationsOptimize data pipelines and infrastructure for performance, cost-effectiveness, and reliabilityMonitor and troubleshoot data pipelines, ensuring high availability and minimal downtimeDesign and implement CI/CD pipelines for automated model training, testing, and deploymentAutomate model deployment and scaling using containerization (Docker) and orchestration tools (Kubernetes)Develop and implement monitoring systems to track AI model performance and manage model driftUse infrastructure automation tools (Terraform, AWS CloudFormation) for cloud resource managementImplement model versioning and experiment tracking (MLflow, DVC) for traceability and reproducibilityCollaborate cross-functionally to integrate AI models into existing applications and servicesStay updated with the latest advancements in data engineering, AI, and cloud technologiesQualificationsBachelor's or Master's in Computer Science, Data Science, or related fieldProven experience in data engineering, focusing on AWS data pipelines and infrastructureStrong proficiency in Python, Java, or Scala; experience with Apache Spark and HadoopExpertise in AWS data services (S3, Glue, Athena, Redshift, EMR)Knowledge of data warehousing, modeling, and management best practicesExperience with data streaming technologies (Apache Kafka, AWS Kinesis)Familiarity with AI and machine learning concepts and frameworks (TensorFlow, PyTorch, scikit-learn)Experience with CI/CD tools, Docker, Kubernetes, and AWS CloudFormationKnowledge of model monitoring tools (Prometheus, Grafana) and MLOps frameworks (Kubeflow, MLflow, AWS SageMaker)Understanding of security best practices for data and AI model deploymentStrong problem-solving, analytical, and communication skills



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