AI/ML Engineer – Azure Platform Modernization
Who We Are
The Role
Among your key responsibilities you will find
- Designing and assessing serverless compute architectures for AI workloads.
- Implementing scalable Azure Databricks Serverless environments.
- Developing and maintaining CI/CD pipelines in Azure DevOps for AI and Databricks workloads.
- Ensuring reliability, observability, monitoring, and optimization of Databricks and serverless services.
- Collaborating closely with Data Science, Cloud Engineering, and DevOps teams as an independent expert - providing consultancy, technical alignment, and best practices for operationalizing AI models efficiently.
Your future at Kyndryl
Who You Are
You’re good at what you do and possess the required experience to prove it. However, equally as important – you have a growth mindset; keen to drive your own personal and professional development. You are customer-focused – someone who prioritizes customer success in their work. And finally, you’re open and borderless – naturally inclusive in how you work with others.
Required Technical and Professional Experience
- Proven experience designing and deploying AI/ML and data engineering solutions on Azure.
- Deep understanding of Azure Databricks architecture, including serverless compute capabilities.
- Hands-on experience with serverless technologies such as Azure Functions, Event Grid, and Logic Apps.
- Proficiency in Python, PySpark, and SQL for data engineering and model integration.
- Strong knowledge of CI/CD, MLOps, and Infrastructure-as-Code using Azure DevOps and Terraform.
- Solid understanding of cloud cost management, scaling strategies, and workload optimization.
- Familiarity with enterprise security, data protection, and compliance requirements for AI workloads.
- Ability to design and implement observability, monitoring, and alerting for Databricks Serverless environments.
Being You
What You Can Expect
Get Referred!
Not included in the source posting: benefits.
Skills
Who can apply
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