Enterprise AI/ML Engineer - MLOps & Cloud

Creative Solutions Services, LLC; Atlanta (GA); On-site; USD 83,000 - 96,000; Full time

Job summary

NTT DATA is seeking an experienced AI/ML Engineer to design, develop, and deploy scalable AI/ML solutions across enterprise applications. The role collaborates with data scientists, data engineers, and business stakeholders to translate requirements into production-ready models and services.

The ideal candidate has strong Python skills, experience with ML frameworks, data processing, and cloud platforms (AWS/Azure/GCP).

Qualifications

• 5+ years of experience in Python development, Data Science, or Machine Learning engineering.

Responsibilities

• Design, develop, train, and deploy Machine Learning models for enterprise use cases.
• Develop data preprocessing, feature engineering, model training, and evaluation pipelines.
• Build and integrate AI/ML services with enterprise applications using APIs and Microservices.
• Evaluate ML algorithms and optimize models for accuracy, performance, and scalability.
• Develop automated ML pipelines for model training, testing, deployment, and monitoring.
• Collaborate with Data Scientists, Data Engineers, and business teams to translate requirements into AI/ML solutions.
• Implement MLOps practices for model versioning, deployment, monitoring, and lifecycle management.
• Work with structured and unstructured datasets from multiple sources.
• Monitor production models and address model performance, drift, and data-quality issues.
• Participate in code reviews, technical design discussions, and Agile delivery activities.

Skills

Python development

Data Science

Machine Learning engineering

Scikit-learn

TensorFlow

PyTorch

SQL

AWS

Azure

GCP

MLOps

Docker

Kubernetes

CI/CD pipelines

MLOps tools

Tools

LangChain

LlamaIndex

Azure OpenAI

Amazon Bedrock

Vertex AI

Databricks

Snowflake

Spark

Job description

NTT DATA is seeking an experienced AI/ML Engineer to design, develop, and deploy scalable AI/ML solutions across enterprise applications. The role collaborates with data scientists, data engineers, and business stakeholders to translate requirements into production-ready models and services.

The ideal candidate has strong Python skills, experience with ML frameworks, data processing, and cloud platforms (AWS/Azure/GCP).