MLOps Engineer - MLEAS

Position Overview:
The MLOps Engineer will establish scalable machine learning operations frameworks and automate the deployment, monitoring, and governance of AI models.

Key Responsibilities:

• Build ML deployment pipelines.
• Implement CI/CD for machine learning workloads.
• Automate model retraining and validation.
• Establish model monitoring and observability.
• Manage ML infrastructure and environments.
• Ensure compliance and governance requirements.

Required Skills:

• MLOps
• MLflow
• Kubeflow
• Docker
• Kubernetes
• Python
• Git Hub Actions
• Azure Dev Ops
• Terraform
• Monitoring Tools

Required Qualifications:

• Bachelor's degree in Computer Science or related field.
• 5+ years of MLOps or ML Engineering experience.

Mandatory Industry Experience:

• Must have prior BFSI experience supporting regulated AI/ML environments, model governance, risk management, fraud analytics, or financial decisioning systems.

For more details reach at