Job Description

Job Title

: Data Scientist (GenAI & Python)

Job Location

: Chennai

Job type:

Full-time.

Description

We are seeking an experienced

Data Scientist

with strong expertise in

Python

and

Generative AI (GenAI)

to design and implement cutting-edge AI/ML solutions. The ideal candidate will have hands-on experience working with

Gemini/OpenAI models

,

Vertex AI

, Big Query

NLP

, and

RAG-based architectures

on

GCP or Azure

platforms.

Key Responsibilities

Develop and deploy

AI/ML and GenAI solutions

using

Gemini/OpenAI

and

Vertex AI

. Build

Retrieval-Augmented Generation (RAG)

solutions using

Vector Databases

,

chunking

, and

embedding

techniques. Create and maintain

CI/CD pipelines

for model deployment and updates. Work extensively with

GCP services

such as

Big Query

,

Form Recognizer

, and

Vertex AI pipelines

. Develop and expose

APIs

for AI services using

FastAPI

or

Django

. Design, manage, and optimize

NoSQL

and

Vector Databases

. Implement

NLP

,

Computer Vision (CV)

, and

Deep Learning

models--preferably for

healthcare data

. Collaborate with cross-functional teams including engineering, analytics, and product teams to deliver scalable AI solutions.

Skills and Qualifications

Strong proficiency in

Python programming

. Hands-on experience with

Generative AI

(Gemini, OpenAI). Expertise in

Vector Databases

,

embedding

, and

retrieval

techniques. Solid understanding of

Machine Learning

,

Deep Learning

,

NLP

, and

Computer Vision

. Experience in

CI/CD pipelines

and

API development

(FastAPI/Django). Familiarity with

NoSQL databases

and

RAG-based architectures

. Experience with

GCP

and/or

Azure

cloud platforms.
Job Type: Full-time

Pay: ₹1,500,000.00 - ₹1,900,000.00 per year

Ability to commute/relocate:

Chennai, Tamil Nadu: Reliably commute or planning to relocate before starting work (Preferred)
Experience:

Data science & Gen Ai: 5 years (Required)
Location:

Chennai, Tamil Nadu (Required)
Willingness to travel:

25% (Preferred)
Work Location: In person