{"schemaVersion":"jobsearcher.job.v1","id":"78329c608caa4adc5182dc0a","url":"https://jobsearcher.com/jobs/78329c608caa4adc5182dc0a","canonicalUrl":"https://jobsearcher.com/jobs/78329c608caa4adc5182dc0a","title":"Machine Learning Engineer (AWS/SageMaker/Dataiku/MLOps)","description":"Machine Learning Engineer (AWS/SageMaker/Dataiku/MLOps)*Visa sponsorship is NOT available, so NO visa candidates please – NO 3rd party vendors reachout – Direct W2 candidates ONLY*Reading, PA OR Tampa, FL | Hybrid (2-3 days onsite per week) | Contract-to-Hire (or Direct Hire, client is flexible)One onsite interview is required | Local candidates to work onsite & appear for onsite interview Please send resume to: aghosh@copiastaffing.com SummaryWe are seeking an experienced Machine Learning Engineer to build, deploy, and operationalize scalable, production-grade machine learning solutions. This is a hands-on engineering role focused on the complete ML lifecycle, from data preparation and model development through production deployment, monitoring, drift detection, and retraining.The ideal candidate will bring strong hands-on experience with Python, AWS, Amazon SageMaker, Dataiku, and MLOps, with a track record of turning ML models into reliable enterprise production solutions.Key ResponsibilitiesBuild end-to-end ML pipelines covering data preparation, feature engineering, training, validation, deployment, inference, monitoring, and retrainingDevelop, train, tune, and deploy ML models using Amazon SageMaker and DataikuOperationalize models developed by Data Scientists and establish scalable MLOps practicesImplement CI/CD, automated ML pipelines, model registries, versioning, deployment automation, and environment promotionMonitor model performance, data quality, feature/data/model drift, and inference healthBuild and support both batch and real-time inference solutionsOptimize models for accuracy, scalability, latency, performance, and costTroubleshoot production issues across data, feature, model, application, and infrastructure layersBuild reusable ML components, APIs, libraries, and pipelinesPartner closely with Data Scientists, Data Engineers, AI Engineers, cloud/platform teams, architects, and business stakeholdersRequired ExperienceStrong hands-on Python 3.11+ development experienceDeep hands-on Amazon SageMaker experience across model development, training, hyperparameter tuning, deployment, inference, monitoring, and lifecycle managementStrong hands-on Dataiku experience for data preparation, feature engineering, ML development, and operational workflowsStrong AWS experience supporting production ML workloads and cloud-native architecturesStrong end-to-end MLOps and production ML lifecycle experienceExperience with model registries, automated ML pipelines, CI/CD, versioning, monitoring, drift detection, and retrainingExperience building batch and real-time ML inference pipelinesExperience with REST APIs, Git, automated testing, Docker/containerization, and CI/CDUnderstanding of AWS security including IAM, secrets management, encryption, authentication/authorization, and least-privilege accessStrong knowledge of ML techniques including classification, regression, clustering, forecasting, anomaly detection, and recommendation systemsNice To HaveExperience with SageMaker Pipelines, Model Registry, Feature Store, Model Monitor, SageMaker Unified Studio, Dataiku Automation, Kubernetes/EKS, model governance, responsible AI, Amazon Bedrock, RAG, or Generative AI is a plus.Relevant AWS certifications are also a plus.","company":"Insource","rawCompany":"insource","city":"Reading","state":"PA","isRemote":false,"isActive":false,"createdAt":"2026-10-09T08:38:18.328Z","occupations":[{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"518210","title":"Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services","slug":"computing-infrastructure-providers-data-processing-web-hosting-and-related-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Machine Learning Engineer (AWS/SageMaker/Dataiku/MLOps)","description":"Machine Learning Engineer (AWS/SageMaker/Dataiku/MLOps)*Visa sponsorship is NOT available, so NO visa candidates please – NO 3rd party vendors reachout – Direct W2 candidates ONLY*Reading, PA OR Tampa, FL | Hybrid (2-3 days onsite per week) | Contract-to-Hire (or Direct Hire, client is flexible)One onsite interview is required | Local candidates to work onsite & appear for onsite interview Please send resume to: aghosh@copiastaffing.com SummaryWe are seeking an experienced Machine Learning Engineer to build, deploy, and operationalize scalable, production-grade machine learning solutions. This is a hands-on engineering role focused on the complete ML lifecycle, from data preparation and model development through production deployment, monitoring, drift detection, and retraining.The ideal candidate will bring strong hands-on experience with Python, AWS, Amazon SageMaker, Dataiku, and MLOps, with a track record of turning ML models into reliable enterprise production solutions.Key ResponsibilitiesBuild end-to-end ML pipelines covering data preparation, feature engineering, training, validation, deployment, inference, monitoring, and retrainingDevelop, train, tune, and deploy ML models using Amazon SageMaker and DataikuOperationalize models developed by Data Scientists and establish scalable MLOps practicesImplement CI/CD, automated ML pipelines, model registries, versioning, deployment automation, and environment promotionMonitor model performance, data quality, feature/data/model drift, and inference healthBuild and support both batch and real-time inference solutionsOptimize models for accuracy, scalability, latency, performance, and costTroubleshoot production issues across data, feature, model, application, and infrastructure layersBuild reusable ML components, APIs, libraries, and pipelinesPartner closely with Data Scientists, Data Engineers, AI Engineers, cloud/platform teams, architects, and business stakeholdersRequired ExperienceStrong hands-on Python 3.11+ development experienceDeep hands-on Amazon SageMaker experience across model development, training, hyperparameter tuning, deployment, inference, monitoring, and lifecycle managementStrong hands-on Dataiku experience for data preparation, feature engineering, ML development, and operational workflowsStrong AWS experience supporting production ML workloads and cloud-native architecturesStrong end-to-end MLOps and production ML lifecycle experienceExperience with model registries, automated ML pipelines, CI/CD, versioning, monitoring, drift detection, and retrainingExperience building batch and real-time ML inference pipelinesExperience with REST APIs, Git, automated testing, Docker/containerization, and CI/CDUnderstanding of AWS security including IAM, secrets management, encryption, authentication/authorization, and least-privilege accessStrong knowledge of ML techniques including classification, regression, clustering, forecasting, anomaly detection, and recommendation systemsNice To HaveExperience with SageMaker Pipelines, Model Registry, Feature Store, Model Monitor, SageMaker Unified Studio, Dataiku Automation, Kubernetes/EKS, model governance, responsible AI, Amazon Bedrock, RAG, or Generative AI is a plus.Relevant AWS certifications are also a plus.","datePosted":"2026-10-09T08:38:18.328Z","dateModified":"2026-10-09T08:38:18.328Z","hiringOrganization":{"@type":"Organization","name":"Insource","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Reading","addressRegion":"PA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"78329c608caa4adc5182dc0a"},"url":"https://jobsearcher.com/jobs/78329c608caa4adc5182dc0a"}}