Cloud AI/ML Ops Engineer
About The Position
ML Ops Expertise: Model lifecycle, pipeline automation, monitoring. Azure Cloud Experience: Azure ML, AKS, Storage, DevOps. .NET Programming: API development, orchestration logic, integration with voice runtime services. Pipeline Architecture: Build modular evaluation pipelines for voice runtime components. Integrate ML-based models for anomaly detection and performance scoring. Enable automated data ingestion, preprocessing, and metric computation. Cloud Infrastructure: Deploy pipelines on Azure using services like: Azure Machine Learning for model training and evaluation. Azure DevOps for CI/CD automation. Azure Storage & Data Lake for logs and telemetry. Azure Kubernetes Service (AKS) for containerized runtime environments. Programming Framework: Implement orchestration and evaluation logic in .NET (C#) for compatibility with existing voice runtime services. Develop APIs for triggering evaluations and retrieving results. ML Ops Integration: Automate model lifecycle management (training, deployment, monitoring). Inco rporate versioning and reproducibility for evaluation models. Implement continuous monitoring for pipeline health and performance. Security & Compliance: Ensure compliance with Responsible AI and data privacy standards. Apply secure authentication and role-based access control for pipeline operations.
Requirements
- Azure Kubernetes Service (AKS)
- .net
- C#
- CI/CD
- Azure ML
- Azure DevOps
- Storage
- ML Ops Expertise: Model lifecycle, pipeline automation, monitoring.
- Azure Cloud Experience: Azure ML, AKS, Storage, DevOps.
- .NET Programming: API development, orchestration logic, integration with voice runtime services.
Responsibilities
- Build modular evaluation pipelines for voice runtime components.
- Integrate ML-based models for anomaly detection and performance scoring.
- Enable automated data ingestion, preprocessing, and metric computation.
- Deploy pipelines on Azure using services like Azure Machine Learning for model training and evaluation, Azure DevOps for CI/CD automation, Azure Storage & Data Lake for logs and telemetry, and Azure Kubernetes Service (AKS) for containerized runtime environments.
- Implement orchestration and evaluation logic in .NET (C#) for compatibility with existing voice runtime services.
- Develop APIs for triggering evaluations and retrieving results.
- Automate model lifecycle management (training, deployment, monitoring).
- Incorporate versioning and reproducibility for evaluation models.
- Implement continuous monitoring for pipeline health and performance.
- Ensure compliance with Responsible AI and data privacy standards.
- Apply secure authentication and role-based access control for pipeline operations.
Benefits
- Discretionary Annual Incentive.
- Comprehensive Medical Coverage: Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans.
- Family Support: Maternal & Parental Leaves.
- Insurance Options: Auto & Home Insurance, Identity Theft Protection.
- Convenience & Professional Growth: Commuter Benefits & Certification & Training Reimbursement.
- Time Off: Vacation, Time Off, Sick Leave & Holidays.
- Legal & Financial Assistance: Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Industry
Professional, Scientific, and Technical Services
Education Level
No Education Listed
Number of Employees
5,001-10,000 employees
