Remote AI/ML Engineer — Enterprise ML & MLOps

NTT DATA, Inc.; Atlanta (GA); On-site; USD 83,000 - 96,000; Full time

Job summary

NTT DATA, Inc. is seeking an experienced AI/ML Engineer in Atlanta/Chicago to design, develop, and deploy scalable AI/ML solutions for enterprise applications.

You will collaborate with data scientists, data engineers, and business stakeholders to translate requirements into production-ready models and services. The role emphasizes strong Python development, ML tooling, MLOps practices, and cloud deployments on AWS, Azure, or Google Cloud.

Qualifications

• 5+ years of Python development, data science, or ML engineering.
• 3+ years developing ML solutions with Scikit-learn, TensorFlow, PyTorch, or similar frameworks.
• 3+ years with data processing, feature engineering, SQL, and model development.
• 2+ years deploying AI/ML solutions on AWS, Azure, or Google Cloud Platform.

Responsibilities

• Design, develop, train, and deploy ML 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 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 performance, drift, and data quality issues.
• Participate in code reviews and Agile delivery activities.

Skills

Python

ML frameworks

Data processing

Cloud platforms

APIs

Microservices

Tools

Scikit-learn

TensorFlow

PyTorch

Job description

NTT DATA, Inc. is seeking an experienced AI/ML Engineer in Atlanta/Chicago to design, develop, and deploy scalable AI/ML solutions for enterprise applications.

You will collaborate with data scientists, data engineers, and business stakeholders to translate requirements into production-ready models and services. The role emphasizes strong Python development, ML tooling, MLOps practices, and cloud deployments on AWS, Azure, or Google Cloud.