Azure ML Ops Consultant - Remote

Nava Software Solutions

United States

NAVA Software solutions is looking for a Azure ML Ops Consultant for one of our clients,

Details:

Azure ML Ops Consultant

Location: 100% Remote

Duration: 6-12 months

Exp : 10 yrs+

Qualifications

Work across the full stack is a must have requirement, moving seamlessly between programming languages and technologies: Python, PySpark, MLFlow, Azure Databricks, ADLS, Snowflake, Azure DevOps, API, Kuberenetes etc
Hands-on experience with cloud analytics services (Primarily Azure)
Infrastructure (Server, Storage, and Database) discovery, design, build, and migration experience
Experience in any of Messaging platforms (Kafka, Azure EventHub, Iot Hub, etc
Experience in Kubernetes and Microservices
Knowledge of various database technologies - SQL, NoSQL, Blob, file system, object store etc
Create and develop CI/CD Pipelines that allow for controlled and continuous enhancement of existing work and new features during both development and production phases
Experience supporting and working with cross-functional teams in an agile environment
Experience in agile product development
Experience in the operationalization of Data Science projects (MLOPs) in Azure

Responsibilities

The MLOps Engineer will work closely with the data scientists working on AI products and solutions across various K-C business units to take the AI models developed and operationalize and own the life cycle management of the models in production for continuous value creation The role will lead our strategic effort of AI life cycle management capabilities such as continuous deployment, model drift and behavior monitoring, model governance, retraining in alignment with business KPIs for continuous value creation for business
Provide data science expertise for AI products, programs across business units within KC
Work with teams to design and build cloud based automated pipeline that run, monitor and retrain AI/ML models using agile methodologies
Have a strategic perspective of how several ML solutions come together against a set of business objectives, product and AI strategy leading to optimal operations of the models
Enhance and improve the code deployment and model monitoring frameworks and project operations documentation
Lead the scalable implementation of solution for AI model governance and model behavior analytics
Support 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 requirements
Create & evolve data & analytics technology roadmap, to align with continuously evolving business needs including overall architecture, capabilities, platforms, tools & governing processes
Create, maintain & communicate positioning/go-forward strategies for data & analytic capabilities/tools
Own strategic technology relationships with technology vendors & external communities/partners
Help define/improve best practices, guidelines & integration with other enterprise solutions

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Vacancy posted 23 hours ago

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