HSO-GS-Azure MLOps Engineer
HSO, India
Job Description
Job Summary:
As an Azure MLOps Engineer, you will be responsible for designing, implementing, and maintaining end-to-end Machine Learning Operations (MLOps) processes and infrastructure on the Azure cloud platform. The ideal candidate will have a strong background in both machine learning and DevOps, with expertise in deploying, monitoring, and managing machine learning models in a production environment.
Responsibilities:
1.MLOps Infrastructure Design and Implementation:
Architect, implement, and maintain MLOps pipelines and workflows on the Azure cloud platform.
Collaborate with data scientists and developers to deploy machine learning models in production environments.
2.Continuous Integration and Continuous Deployment (CI/CD):
Implement CI/CD pipelines for machine learning models, ensuring efficient and automated deployment processes.
Integrate model versioning and tracking within CI/CD workflows.
3.Monitoring and Logging:
Implement monitoring solutions for deployed machine learning models to ensure optimal performance and reliability.
Set up logging and alerting mechanisms to detect and address issues proactively.
4.Scalability and Efficiency:
Optimize machine learning workloads for scalability and cost-effectiveness on Azure.
Implement resource scaling strategies based on workload demands.
5.Security and Compliance:
Implement security best practices for machine learning models and data on Azure.
Ensure compliance with regulatory requirements and company policies.
6.Collaboration and Documentation:
Collaborate with cross-functional teams, including data scientists, software engineers, and IT operations.
Create and maintain comprehensive documentation for MLOps processes and configurations.
Requirements
Qualifications:
- Bachelor's or Master's degree in Computer Science, Data Science, or a related field.
- Proven experience in deploying and managing machine learning models in a production environment.
- Strong proficiency in Azure services, including Azure Machine Learning, Azure DevOps, and Azure Kubernetes Service (AKS).
- Expertise in CI/CD practices and tools (e.g., Azure DevOps, Jenkins).
- Knowledge of containerization technologies (Docker) and orchestration tools (Kubernetes).
- Familiarity with version control systems (Git) and model versioning concepts.
- Understanding of security and compliance considerations in MLOps.
Benefits
Health Insurance
Food Coupons
Gym and Telephone/Internet bill Reimbursement
Leave Travel Allowance (can be claimed only twice in a block of FOUR calendar years)
PF
NPS (Optional)
Great Work Culture