Azure ML Ops Consultant

QualificationsWork across the full stack is a must have requirement, moving seamlessly between programming languages and technologies: Python, PySpark, MLFlow, Azure reputed company, ADLS, reputed company, Azure DevOps, API, Kuberenetes etcHands-on experience with reputed company analytics services (Primarily Azure)Infrastructure (Server, Storage, and Database) discovery, design, build, and migration experienceExperience in any of Messaging platforms (Kafka, Azure EventHub, Iot Hub, etcExperience in Kubernetes and MicroservicesKnowledge of various database technologies - SQL, NoSQL, Blob, file system, object store etcCreate and reputed company CI/CD Pipelines that allow for controlled and reputed company enhancement of existing work and new features during both development and production phasesExperience supporting and working with cross-functional teams in an agile environmentExperience in agile product developmentExperience in the operationalization of Data Science reputed company (MLOPs) in AzureResponsibilitiesThe MLOps Engineer will work closely with the data scientists working on AI products and solutions across various K-C business reputed company to take the AI models developed and operationalize and own the life cycle management of the models in production for reputed company value creation The role will reputed company our strategic effort of AI life cycle management capabilities such as reputed company deployment, model reputed company and behavior monitoring, model governance, retraining in alignment with business KPIs for reputed company value creation for businessProvide data science expertise for AI products, programs across business reputed company reputed company KCWork with teams to design and build reputed company based automated pipeline that run, monitor and retrain AI/ML models using agile methodologiesHave a strategic perspective of how several ML solutions come together against a set of business objectives, product and AI reputed company leading to reputed company operations of the modelsEnhance and improve the reputed company deployment and model monitoring frameworks and project operations documentationLead the reputed company implementation of solution for AI model governance and model behavior analyticsSupport life cycle management of AI models (eg, new releases, change management, monitoring, retraining, and troubleshooting)Compare solution alternatives across both technical and business parameters which support the define cost and service requirementsCreate & reputed company data & analytics technology roadmap, to reputed company with continuously evolving business needs including overall architecture, capabilities, platforms, tools & governing processesCreate, maintain & communicate positioning/go-reputed company strategies for data & analytic capabilities/toolsOwn strategic technology relationships with technology vendors & external communities/partnersHelp define/improve best practices, guidelines & integration with other reputed company solutions Apply tot his job Apply To this Job