AI ML Data Engineer

Job Title: AI/ML Data Engineer (AI Platform)

Location: Bangalore

Experience: 7+ Years (STRICTLY)

Employment Type: Full Time

Notice Period: Immediate / Short Notice Preferred

About the Company

Our client is a trusted global innovator of IT and business services, present in 50+ countries. They specialize in digital & IT modernization, consulting, managed services, and industry-specific solutions. With a commitment to long-term success, they empower clients and society to move confidently into the digital future.

Job Description

Must Have Skills:

• Python
• LLM Fine-tuning
• Retrieval Augmented Generation (RAG)
• AI Agents / GenAI Applications
• MLOps lifecycle implementation
• Model optimization
• PyTorch / TensorFlow

Minimum Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related technical field.
• 7+ years of experience in AI/ML engineering, data engineering, or machine learning platform development.
• Hands-on experience working with Large Language Models (LLMs) and Generative AI systems.
• Strong programming skills in Python.
• Experience implementing MLOps pipelines and lifecycle management.
• Experience integrating AI/ML models with enterprise data systems.

Preferred Qualifications:

• Experience with OpenShift AI / OpenShift / AWS SageMaker / AWS Bedrock.
• Experience working with Vector Databases (Redis or similar).
• Hands-on experience with Kubernetes / containerized ML deployments.
• Experience building RAG pipelines and AI agents.
• Exposure to CI/CD tools such as Jenkins or ArgoCD.
• Experience deploying and serving models using:
• Triton Inference Server
• vLLM
• TensorRT

Responsibilities:

• Build, optimize, and deploy AI/GenAI models for enterprise banking use cases.
• Design and implement LLM fine-tuning pipelines.
• Develop and maintain RAG systems and AI agents.
• Implement and manage the MLOps lifecycle including model training, deployment, monitoring, and optimization.
• Integrate AI models with internal banking datasets and data pipelines.
• Deploy models on on-premise AI infrastructure using Kubernetes / OpenShift.
• Optimize model performance using model serving frameworks.
• Collaborate with platform, data, and engineering teams to scale AI capabilities across the organization.

Platform Overview

The internal AI platform is used to:

• Build and deploy Large Language Models (LLMs)
• Develop AI agents and Generative AI applications
• Manage AI ecosystem and ML pipelines
• Run on-premise AI models instead of external AI services

Important Note (Please Read Before Applying)

🚫 Do NOT apply if:

• You only have Big Data / Cloudera / Spark experience
• You do not have AI/ML or GenAI experience
• You do not have hands-on LLM or MLOps experience
• You do not meet the 7+ years experience requirement

✅ Apply ONLY if you meet ALL criteria above. Random / irrelevant applications will not be processed.