MLOps Engineer

NTT DATA North America is a global innovator of business and technology services, seeking an MLOps Engineer to develop ML applications and ensure successful model deployments. The role involves leveraging expertise in ML frameworks and cloud services to create infrastructure for actionable insights and communicate technical concepts effectively to clients.

Responsibilities:

• Exercise expertise in ideating and developing ML applications on prediction, recommendation, text analytics, computer vision, bots, and document intelligence
• Demonstrate deep knowledge of ML frameworks such as TensorFlow, PyTorch, Keras, Spacy, and scikit-learn
• Employ technical knowledge and hands-on experience with Azure ML Studio and Azure Kubernetes Service
• Experience in deploying Azure cloud services using Terraform templates with strong knowledge of DevOps principles and automated deployments
• Leverage advanced knowledge of Python open-source software stack such as Django or Flask, Django Rest or FastAPI, etc
• Work on model inferencing, validation and deployments to ensure models are deployed with the appropriate levels of validation and quality
• Create and maintain infrastructure to ingest, normalize, and combine datasets for actionable insights
• Interact at appropriate levels to ensure client satisfaction and project success
• Communicate complex technical concepts clearly to non-technical audiences

Requirements:

• 8+ Years experience with: MLOps
• Azure Kubernetes
• Argo / Bento
• Azure ML Studio
• Model Inferencing
• Exercise expertise in ideating and developing ML applications on prediction, recommendation, text analytics, computer vision, bots, and document intelligence
• Demonstrate deep knowledge of ML frameworks such as TensorFlow, PyTorch, Keras, Spacy, and scikit-learn
• Employ technical knowledge and hands-on experience with Azure ML Studio and Azure Kubernetes Service
• Experience in deploying Azure cloud services using Terraform templates with strong knowledge of DevOps principles and automated deployments
• Leverage advanced knowledge of Python open-source software stack such as Django or Flask, Django Rest or FastAPI, etc
• Work on model inferencing, validation and deployments to ensure models are deployed with the appropriate levels of validation and quality
• Create and maintain infrastructure to ingest, normalize, and combine datasets for actionable insights
• Interact at appropriate levels to ensure client satisfaction and project success
• Communicate complex technical concepts clearly to non-technical audiences