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Data Scientist - Generative AI

NS Global Corporation
Bangalore
7 - 12 Years

Posted on: 23/07/2025

Job Description

Role : Data Scientist


We are looking for a highly skilled and experienced Data Scientist who has hands-on expertise in building scalable data-driven applications using modern AI/ML techniques. The ideal candidate will have solid experience working in fast-paced startup environments, building and deploying AI applications using Databricks, LLM models (like LLaMA), Vector Databases, and scripting in Python with backend integration using PostgreSQL.


Key Responsibilities :


- Design and implement machine learning and generative AI models for real-world use cases.

- Work with LLM models such as LLaMA for fine-tuning and inference.

- Build intelligent applications integrating Vector Databases (e.g., FAISS, Pinecone, Milvus, etc.).

- Develop scalable data pipelines and model training workflows using Databricks.

- Write production-grade Python scripts for data ingestion, transformation, and model deployment.

- Collaborate with AI Engineers and product teams to rapidly prototype and deliver high-impact solutions.

- Integrate AI applications with databases such as PostgreSQL and RESTful APIs.

- Ensure the delivery of AI solutions in a fast-paced, startup-like agile environment.


Required Skills & Qualifications :


- 7+ years of experience as a Data Scientist or AI Engineer.

- Strong experience with Databricks building and managing data pipelines, ML workflows.

- Hands-on expertise in Generative AI and Large Language Models (LLMs) such as LLaMA, GPT,

Mistral, etc.

- Proficient in integrating and querying Vector Databases.

- Expert-level skills in Python for data science and scripting.

- Solid knowledge of PostgreSQL and backend database integration.

- Experience with AI toolsets and open-source libraries (Hugging Face, LangChain,

Transformers, etc.).

- Ability to work independently and thrive in a startup-like environment.


Preferred Qualifications :


- Experience in deploying AI solutions to production (MLOps).

- Familiarity with cloud services (AWS, Azure, or GCP).

- Contributions to open-source AI projects or research publications.


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