AI/ML Engineer

Tata Consultancy Services; Bengaluru; On-site; INR 1,800,000 - 2,800,000; Full time

Job summary

Tata Consultancy Services in Bengaluru is seeking an experienced AI/ML Engineer to design, train, deploy, and monitor scalable ML models, with strong GenAI and AWS Cloud expertise. You will build end-to-end ML pipelines, implement MLOps, and collaborate with stakeholders to deliver enterprise-grade AI solutions.

The role emphasizes production-grade deployment on AWS, model evaluation, feature engineering, and staying ahead in GenAI technologies and AI-driven automation.

Qualifications

• 5–8 years IT experience with 3+ years in AI/ML.
• Hands-on experience deploying production-grade AI/ML solutions.
• Experience with GenAI and AWS cloud tech is preferred.

Responsibilities

• Design, train, deploy, and monitor ML models using AWS SageMaker.
• Build end-to-end ML pipelines including data preprocessing, feature engineering, model training, and deployment.
• Develop predictive analytics solutions using Scikit-learn, TensorFlow, PyTorch, XGBoost, and LightGBM.
• Build GenAI solutions using GPT APIs, LangChain, LlamaIndex, RAG frameworks, and AI Agents.
• Implement MLOps practices including CI/CD, model versioning, monitoring, and automated deployments.
• Integrate AI/ML solutions with AWS services such as S3, Lambda, Glue, IAM, CloudWatch, and REST APIs.
• Collaborate with business and technical stakeholders to deliver scalable AI-driven solutions.

Skills

Python

SQL

Model evaluation

Feature engineering

Deployment best practices

Tools

Scikit-learn

TensorFlow

PyTorch

XGBoost

LightGBM

GPT APIs

LangChain

LlamaIndex

RAG

AI Agents

Prompt Engineering

Job description

Looking for an experienced AI/ML Engineer with strong expertise in Machine Learning, Generative AI, and AWS cloud technologies. The candidate will be responsible for building, deploying, and optimizing scalable ML solutions, developing GenAI applications, and implementing MLOps best practices for enterprise use cases.

Key Responsibilities

• Design, train, deploy, and monitor ML models using AWS SageMaker.
• Build end-to-end ML pipelines including data preprocessing, feature engineering, model training, and deployment.
• Develop predictive analytics solutions using Scikit-learn, TensorFlow, PyTorch, XGBoost, and LightGBM.
• Build GenAI solutions using GPT, Llama, Gemini, LangChain, LlamaIndex, AI Agents, and RAG frameworks.
• Implement MLOps practices including CI/CD, model versioning, monitoring, and automated deployments.
• Integrate AI/ML solutions with AWS services such as S3, Lambda, Glue, IAM, CloudWatch, and REST APIs.
• Collaborate with business and technical stakeholders to deliver scalable AI-driven solutions.

Required Skills

• Programming: Python, SQL
• ML Frameworks: Scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM
• Generative AI: GPT APIs, LangChain, LlamaIndex, RAG, AI Agents, Prompt Engineering
• Strong understanding of model evaluation, feature engineering, and deployment best practices

Good to Have

• Computer Vision and Multimodal AI
• Experience in enterprise automation, RFPs, and PoC development

Preferred Experience

• 5-8 years overall IT experience with 3+ years in AI/ML.
• Hands-on experience deploying production-grade AI/ML solutions on AWS.
• Experience building GenAI applications and AI-powered automation solutions.