*AI Ops Engineer II

Zurich Insurance-posted 3 months ago
Full-time • Mid Level
Remote • Schaumburg, IL
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Zurich (Schaumburg, IL) seeks an AI Ops Engineer II to participate in the production deployment and automation of Generative AI solutions, serving as an AI operations subject matter expert for other technical teams within the Data and Analytics unit. The position offers the option to work remotely from anywhere in the U.S.

  • Research industry best practices, evaluate new technologies, develop standards and engineering best practices and recommend innovative solutions that support automation and improve platform resiliency and fault tolerance of critical applications (10%)
  • Participate in deployment of Generative AI Platform Capabilities with responsible for AI model delivery to cloud platforms (Databricks, MLflow, Azure ML) (40%)
  • Act as an expert resource for other technical teams within Data & Analytics (20%)
  • Assist with hardware and capacity planning, analysis and forecasts for your portfolio of applications with focus on highest availability, scalability, performance, and timely delivery (10%)
  • Execute on roadmaps that align with technology and business strategy (10%)
  • Participate in day-to-day standups for platform capability build (5%)
  • Provide SME guidance for data science teams (5%)
  • Bachelor's degree, or foreign equivalent, in Computer Science, Applied Data Analytics, or a closely related field of study, plus 5 years of experience in the job offered, or as a ML Engineer, DevOps Engineer, Data Analytics Engineer, Software Engineer, or similar position participating in the production deployment.
  • Alternatively, a Master's degree, or foreign equivalent, in Computer Science, Applied Data Analytics, or a closely related field of study, plus 3 years of experience in the job offered, or as a ML Engineer, DevOps Engineer, Data Analytics Engineer, Software Engineer, or similar position participating in the production deployment.
  • 3 years of experience with creating Azure services Function Apps and Logic Apps to enable serverless workloads, managing both synchronous and asynchronous request calls.
  • 3 years of experience managing releases through continuous integration and CI/CD pipelines by creating pull requests and pushing Docker images into the container registry within a fully functional DevOps repository across multiple environments.
  • 3 years of experience using Python, SQL, Spark, Azure Portal, DevOps, and VS Code.
  • 2 years of experience working with Dataiku DSS and Azure Databricks.
  • 2 years of experience deploying real-time and batch scoring predictive models using MLflow, serverless endpoints and Databricks Workflows.
  • 2 years of experience implementing change data capture and utilizing Delta Live Tables to define data transformations while automating data processing pipelines.
  • 2 years of experience working with MLflow tracking for model monitoring, as well as registering models via Unity Catalog for data governance, automating refreshing of hyperparameters based on production metrics.
  • 2 years of experience developing automated scripts to monitor health status and trigger alerts for various app instances using custom metrics, using deployment slots for versioning across different environments.
  • 2 years of experience diagnosing workflows within Azure Logic Apps and logging runtime data to Log Analytics workspace, Azure Storage Account, or Azure Event Hub, while configuring Azure Monitor Logs.
  • 2 years of experience working with open-source LLM models, OpenAI endpoints, and various LangChain methods.
  • 2 years of experience implementing and automating testing frameworks for pipelines, including regression testing, load/stress testing, automated rollback, unit testing, and integration testing.
  • 2 years of experience using Azure Document Intelligence Optical Character Recognition (OCR) models to extract both printed and handwritten text from PDFs, scanned images, .xlsx, .pptx, .html files.
  • 2 years of experience using Azure Prompt Flow for model orchestration, deployment, and testing, streamlining AI application development.
  • 2 years of experience analyzing various architectural models and translating them into detailed process flows for clearer understanding and implementation.
  • Comprehensive employee benefits package for employees as well as eligible dependents
  • Competitive compensation
  • Short-term incentive bonuses and merit increases
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