ML Ops Engineer

Hi,This is Vamshi ,from Software Technology We have a job opening with our client for position ML Ops Engineer If you are available and looking for any new opportunities, please send me your updated resume for below position ASAP.Job Title: ML Ops Engineer Location: Austin, TX (Hybrid)Duration: Longterm ContractLooking for locals in TexasLook for Senior hands on consultantsKey must have skills: Python, AWS SageMaker, SageMaker Pipelines, ML flow, Kubeflow, Docker, Kubernetes, Amazon EKS,CI/CD, CodePipeline, CodeBuild, MLOps, Model Registry, Model Monitoring, Drift Detection, Step Functions,Lambda,S3,CloudWatch,CloudFormation,Infrastructure-as-Code Job DescriptionWe are looking for an experienced MLOps Engineer to design, build, and manage scalable machine learning infrastructure on AWS. This role will drive the end-to-end operationalization of ML models — from automated training pipelines and experiment tracking to production deployment, monitoring, and continuous retraining. The ideal candidate will bridge the gap between data science and engineering, establishing robust MLOps practices that ensure reliable, repeatable, and efficient delivery of ML solutions at scale using AWS-native services and industry-leading tools like SageMaker, Kubeflow, and MLflow.Roles & ResponsibilitiesJob DescriptionRequired Skills & QualificationsProficiency in production-grade machine learning system development, deployment, and MLOps practices on AWSStrong experience with Python and ML frameworks such as TensorFlow or PyTorchFamiliarity with containerization and orchestration tools like Docker and Kubernetes (including Amazon EKS)Hands-on experience with CI/CD pipelines using AWS-native tools such as CodePipeline, CodeBuild, and CodeDeployAdvanced knowledge of AWS cloud services, particularly SageMaker, Bedrock, Lambda, Step Functions, and S3Expertise in MLOps tools and platforms including Kubeflow, MLflow, and AWS SageMaker Pipelines for end-to-end model lifecycle managementExperience with model versioning, experiment tracking, model registry, and automated retraining workflowsFamiliarity with AWS infrastructure-as-code tools such as CloudFormation or CDKStrong understanding of model monitoring, drift detection, and A/B testing in production environmentsStrong analytical and troubleshooting skills to maintain high system reliability using CloudWatch, X-Ray, and AWS-native observability toolsRoles & ResponsibilitiesDesign, implement, and manage AWS-based MLOps infrastructure to support large-scale machine learning workflowsBuild and maintain end-to-end ML pipelines using SageMaker Pipelines, Step Functions, and Kubeflow for automated training, validation, and deploymentImplement model versioning, experiment tracking, and model registry practices using MLflow and SageMaker Model RegistryDevelop and maintain CI/CD pipelines for ML models, ensuring seamless integration from development to productionDemonstrate hands-on expertise in Python and frameworks like TensorFlow or PyTorch, with deployment on SageMaker endpointsUtilize Docker, Amazon EKS, and AWS-native CI/CD tools to streamline ML deployment and operationsLeverage core AWS services such as S3, EC2, Lambda, Glue, and Athena for building and scaling data and ML infrastructureDeploy, manage, and optimize machine learning models in production using SageMaker real-time and batch inference endpointsImplement automated model monitoring, drift detection, and retraining triggers to maintain model health in productionSet up A/B testing and canary deployment strategies for safe model rolloutsCollaborate with data scientists and engineering teams to standardize MLOps practices and enhance performance across the AWS ecosystemMonitor system and model performance using CloudWatch, CloudTrail, and X-Ray, troubleshoot issues, and ensure high availability and reliabilityStay informed about the latest AWS service releases, MLOps best practices, and advancements in ML operations toolingSkills To Be Evaluated OnPython,AWS SageMaker,SageMaker Pipelines,MLflow,Kubeflow,Docker,Kubernetes,Amazon EKS,CI/CD,CodePipeline,CodeBuild,MLOps,Model Registry,Model Monitoring,Drift Detection,Step Functions,CloudFormation,Infrastructure-as-CodeThanks,Vamshi ThangadpalliTechnical RecruiterEmail: vamshi.t@stiorg.com | Web: www.stiorg.comhttps://www.linkedin.com/in/vamshi-thangadpalli-3a0415251/100 Overlook Center, Suite 200Princeton, NJ 08540.