Walk-in | AI/ML (Bengaluru)

Tata Consultancy Services Limited; Bengaluru; Vor Ort; INR 2.500.000 - 4.500.000; Vollzeit

Zusammenfassung

Tata Consultancy Services Limited in Bengaluru is seeking an experienced AI/ML Engineer (6-12 years) to join a walk-in drive. The role involves building, deploying, and monitoring scalable ML solutions using AWS SageMaker and modern MLOps practices.

You will develop GenAI applications, design end-to-end ML pipelines, and integrate ML solutions with AWS services while collaborating with business and technical stakeholders to deliver enterprise-grade AI systems.

Qualifikationen

• Proficiency in Python and SQL for model development.
• Extensive experience with ML frameworks and generative AI.
• Experience deploying ML solutions on AWS and implementing MLOps.
• Strong data engineering capabilities (Pandas, NumPy).

Aufgaben

• Design, train, deploy, and monitor ML models on AWS SageMaker.
• Build end-to-end ML pipelines: data prep, feature engineering, training, deployment.
• Develop predictive analytics with Scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM.
• Create GenAI solutions using GPT, LangChain, LlamaIndex, RAG, AI Agents.
• Apply MLOps: CI/CD, versioning, monitoring, automated deployments.
• Integrate AI/ML with AWS services (S3, Lambda, Glue, IAM, CloudWatch, REST APIs).
• Collaborate with stakeholders to deliver scalable AI-driven solutions.

Kenntnisse

Python

SQL

Scikit-learn

TensorFlow

PyTorch

XGBoost

LightGBM

GPT APIs

LangChain

LlamaIndex

RAG

AI Agents

Prompt Engineering

SageMaker

S3

Lambda

Glue

CloudWatch

IAM

SageMaker Pipelines

Model Registry

Docker

Jenkins

Git

Pandas

NumPy

Athena

Tools

Docker

Jenkins

Git

Jobbeschreibung

Walk-In Drive | AI/ML Engineer (6-12 Years) | Bengaluru

Time : 9:30am - 1:30Pm

Date : 24th October 2026

Location: Bengaluru (venue details will be shared later)

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
• Cloud: AWS SageMaker, S3, Lambda, Glue, CloudWatch, IAM
• MLOps: SageMaker Pipelines, Model Registry, Docker, Jenkins, Git
• Data Engineering: Pandas, NumPy, Athena
• Strong understanding of model evaluation, feature engineering, and deployment best practices

Good to Have

• Geospatial Analytics (ArcGIS, GeoPandas, GDAL, OSMnx)
• 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.