Senior AI Engineer

NTT DATA BUSINESS SOLUTIONS; Bengaluru; On-site; INR 2,500,000 - 4,000,000; Full time

Job summary

NTT DATA BUSINESS SOLUTIONS in Bangalore seeks a Senior AI Engineer to design, develop, and deploy production-grade AI/ML solutions. You will work with Python, SQL, and modern ML frameworks to build scalable data pipelines and training workflows.

You will implement MLOps practices, including CI/CD and automated retraining, and develop NLP/LLM solutions using Hugging Face transformers. Collaboration with data engineers and stakeholders is essential, with mentoring of junior engineers.

Qualifications

• Experience designing and deploying AI/ML solutions in production.
• Strong Python, SQL, and ML framework proficiency.
• Experience with MLOps, CI/CD, model deployment and monitoring.
• Experience with NLP/LLMs and Generative AI; Hugging Face ecosystem.

Responsibilities

• Design, develop, and optimize AI/ML solutions using Python, SQL, and ML frameworks.
• Build scalable data pipelines and training workflows with high performance and reliability.
• Implement MLOps practices including CI/CD, model deployment, monitoring, and automated retraining.
• Develop, fine-tune, and deploy NLP/LLM/Generative AI solutions using Hugging Face and Transformers.
• Collaborate with data engineers, architects, and business stakeholders to translate requirements into production-grade AI solutions while mentoring junior engineers.

Skills

Python

SQL

ML frameworks

MLOps

NLP/LLM

Tools

Hugging Face

Transformers

Embedding models

Job description

Job Summary

We are currently seeking a Senior AI Engineer to join our team in Bangalore, Karnataka, India.

Responsibilities

• Design, develop, and optimize AI/ML solutions using advanced Python programming, SQL, and modern machine learning frameworks to solve complex business problems.
• Build scalable data pipelines, feature engineering frameworks, and model training workflows while ensuring high performance, reliability, and maintainability.
• Implement and manage MLOps practices including CI/CD, model deployment, monitoring, versioning, governance, and automated retraining processes.
• Develop, fine-tune, and deploy NLP, LLM, and Generative AI solutions using Hugging Face, Transformers, embedding models, and related open-source ecosystems.
• Collaborate with data engineers, architects, and business stakeholders to translate requirements into production-grade AI solutions while mentoring junior engineers and promoting engineering best practices.