Walk-in | Generative AI/ML Developer

Tata Consultancy Services; Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Benefits offered by this job

Walk-in Drive

Job summary

Tata Consultancy Services (TCS) invites candidates for a Gen AI/ML Developer Walk-In Drive in Bangalore on 22nd Aug 2026. The face-to-face session targets talented developers with strong Gen AI/ML foundations. The day runs 9AM–2PM and focuses on practical skills in Python, ML, and cloud technologies.

The role expects 4–12 years of experience with hands-on work in Python, SQL, and modern AI tooling, including LLMs, RAG, LangChain, and ML pipelines.

Qualifications

• Python (Mandatory).
• SQL knowledge required.
• Java/Scala (Good to Have).
• Gen AI/ML skills: LLMs, Prompt Engineering, RAG, LangChain, Vector DBs.
• ML/DL: Scikit-learn, TensorFlow, PyTorch, NLP, model optimization.
• Cloud & MLOps: AWS/Azure/GCP, SageMaker, Docker, Kubernetes, CI/CD for ML.
• Data processing: Pandas/NumPy; Spark/PySpark.
• Databases: SQL Server, PostgreSQL, MySQL, MongoDB, DynamoDB.

Skills

Gen AI/ML Developer

Python

SQL

Java/Scala

LLMs

Prompt Engineering

RAG

LangChain

Vector Databases

Scikit-learn

TensorFlow

PyTorch

NLP

DL Concepts

Feature Engineering

Model Optimization

AWS

Azure

GCP

SageMaker

Vertex AI

MLflow

Docker

Kubernetes

CI/CD for ML

Pandas

NumPy

Spark/PySpark

SQL Server

PostgreSQL

MySQL

MongoDB

DynamoDB

Tools

Docker

Kubernetes

SageMaker

Azure AI Studio

Vertex AI

Job description

Greetings from TCS Recruitment Team!

Face to Face For all those Gen AI/ML Developer we are coming bigger with the plan of Walk In Drive on 22nd Aug,2026 (Saturday) in Bangalore

It is a Face to Face interview planned to attract great Talents in Gen AI/ML Developer We believe that your skills and expertise are a better match for the skills we are looking for.

Skill: Gen AI/ML Developer(Face to Face)

Years of experience: 4 to 12 Years

Location: Bangalore

Date: 22nd Aug,2026 (Saturday)

Drive Time: 9AM to 2 PM

JD:-

Programming Languages

• Python (Mandatory)
• SQL
• Java/Scala (Good to Have)

Generative AI

• Large Language Models (LLMs)
• Prompt Engineering
• Retrieval-Augmented Generation (RAG)
• AI Agents and Agentic Frameworks
• LangChain / LlamaIndex
• Vector Databases (Pinecone, ChromaDB, FAISS, Weaviate)

Machine Learning & Deep Learning

• Scikit-learn
• TensorFlow / PyTorch
• NLP, Classification, Regression Models
• Deep Learning Concepts
• Feature Engineering and Model Optimization

Cloud & MLOps

• AWS / Azure / GCP
• SageMaker, Azure AI Studio, Vertex AI
• MLflow
• Docker, Kubernetes
• CI/CD for ML Pipelines

Data Engineering

• Data Processing using Pandas, NumPy
• ETL Pipelines
• Data Warehousing Concepts
• Knowledge of Spark/PySpark

Databases

• SQL Server
• PostgreSQL
• MySQL
• NoSQL Databases (MongoDB, DynamoDB)