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KANINI - Senior Data Scientist - Artificial Intelligence/Machine Learning

Posted on: 31/08/2025

Job Description

Role : Senior Data Scientist

Experience : 6 Years -12 Years

Location : Chennai, Coimbatore, Pune, Bangalore

Notice Period : 30 Days

Job Description :

Join our high-performing team, honored with the prestigious "Outstanding Data Engineering Team" Award at DES 2025 for setting new benchmarks in data excellence.

About the Role :

We are looking for a skilled and passionate Data Scientist who brings hands-on expertise in Python programming, and Generative AI (GenAI) to help us design, build, and scale intelligent, AI-powered solutions.


The ideal candidate will have deep experience with NLP, Computer Vision (CV), LLMs, FastAPI, vector databases, and modern machine learning pipelines.

Key Responsibilities :

- Design and implement AI/ML models for solving real-world business problems using Python and Azure ML.

- Develop and deploy RAG-based solutions integrating embedding techniques, chunking, and retrieval strategies.

- Work on OpenAI/GenAI-based models and fine-tune for specific enterprise use cases.

- Build and consume REST APIs using FastAPI or Django.

- Leverage Azure Form Recognizer for intelligent document processing.

- Implement CI/CD pipelines for model deployment and automation.

- Work with NoSQL and Vector Databases to store and retrieve high-dimensional data.

- Collaborate with cross-functional teams to build scalable and robust ML pipelines.

- Apply Deep Learning and NLP/CV techniques to enhance product features.

Primary Skills Required :

- Strong expertise in Python programming

- Experience with GCP Cloud services.

- Hands-on with FastAPI, framework

- Good understanding of CI/CD pipelines

- Proficiency in GenAI and OpenAI models

- Expertise in NLP, Computer Vision, Machine Learning, and Deep Learning

- Familiarity with NoSQL Databases (e.g., MongoDB, Cosmos DB)

- Experience with Vector Databases (e.g., FAISS, Pinecone, Qdrant)

- Knowledge of embedding & chunking techniques

- Experience in building RAG (Retrieval-Augmented Generation) based solutions

- Strong grasp of retrieval methods and information retrieval


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