Data & Business Insights Analyst

NTT America, Inc.; Chennai; Sur place; INR 1 200 000 - 1 700 000; Plein temps

Résumé du poste

NTT America, Inc. in Chennai seeks an experienced AI/ML engineer to design, develop, test, and deploy machine learning, Generative AI, and AI-driven applications aligned with business requirements.

You will build reusable Python components, APIs, and services, integrate LLM-based solutions with prompt engineering, RAG, embeddings and vector databases, and work across Azure, AWS, or Google Cloud to deliver end-to-end AI solutions.

Qualifications

• Experience designing ML and Generative AI applications.
• Experience integrating LLM-based solutions using prompt engineering, RAG, embeddings.

Responsabilités

• Design, develop, test, and deploy ML, Generative AI and AI-driven applications.
• Develop and integrate LLM-based solutions with prompt engineering, RAG, embeddings, and AI APIs.
• Build reusable Python components, APIs and services for AI/ML applications.
• Perform data prep, feature engineering, model training, evaluation and monitoring.

Connaissances

Python

LLMs

Prompt engineering

RAG

Embeddings

APIs

Cloud (Azure/AWS/GCP)

Generative AI

Outils

Azure

AWS

Google Cloud

REST APIs

Databases

Description du poste

Job Description:

1. Design, develop, test, and deploy machine learning, Generative AI, and AI-driven applications based on business requirements.

2. Develop and integrate LLM-based solutions using prompt engineering, RAG, embeddings, vector databases, and AI APIs.

3. Build reusable Python-based components, APIs, and services to support AI and machine learning applications.

4. Perform data preparation, feature engineering, model training, evaluation, optimization, and performance monitoring.

5. Work with cloud-based AI and data services, preferably Microsoft Azure, AWS, or Google Cloud.

6. Develop and integrate REST APIs, databases, enterprise applications, and external data sources into AI solutions.

7. Implement responsible AI practices including security, data privacy, model governance, explainability, and monitoring.

8. Collaborate with data engineers, software developers, architects, business analysts, and stakeholders to deliver end-to-end AI solutions.

9. Troubleshoot model, application, and integration issues and continuously improve solution accuracy, scalability, reliability, and performance.

10. Stay current with emerging AI, Generative AI, Agentic AI, machine learning frameworks, and industry best practices and contribute to AI innovation initiatives.