Data Scientist

Ganit Business Solutions; Mumbai; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

Ganit Inc in Mumbai seeks an experienced Generative AI Engineer with 5+ years of hands-on experience to join our dynamic Data Science team. You will design, deploy and manage LLM-based solutions, build autonomous AI agents, and deliver scalable AI applications on cloud platforms to drive business impact.

You will work on Retrieval-Augmented Generation, vector databases, model evaluations, and stay updated with Gen AI research while collaborating with cross-functional teams and ensuring

Qualifications

• 5+ years of hands-on experience in machine learning and data science.
• Proficient in Python and ML libraries (scikit-learn, pandas, Hugging Face Transformers).

Skills

Python

Machine Learning

NLP

Communication

Education

Bachelor's or Master's in CS/DS/AI

Tools

LangGraph

Crew AI

Phidata

AutoGen

Streamlit

Gradio

AWS Bedrock

Pinecone

Job description

About Ganit Inc :

• Founded by senior industry experts, Ganit is the fastest-growing data science company in Chennai with offices in Bengaluru, Mumbai & New Jersey.
• Ganit has flipped the data science value chain. We don't start with a technique. For us, consumption comes first. With this philosophy we have successfully scaled from being a small start-up to 200 resource company with clients in the US, Singapore, Africa, UAE, and India.
• We are helping Fortune 500 companies across the globe to maximize their Decision-Making Power (#DMP). We are looking for experienced data enthusiasts who can make data talk to them.

Job Overview:

We are looking for a highly skilled and self-motivated Generative AI Engineer with over 5 years of experience to join our dynamic Data Science team. The ideal candidate will bring deep expertise in Generative AI, along with a solid foundation in Data Science. You should have hands-on experience in designing, deploying, and managing Large Language Model (LLM)-based solutions, developing intelligent AI agents, and delivering scalable AI applications on cloud platforms. In this role, you will be instrumental in building end-to-end intelligent systems that drive tangible business impact across diverse domains.

Key Responsibilities:

Qualifications:

• Bachelors or Masters degree in Computer Science, Data Science, AI, or a related field.
• 5+ years of hands-on experience in machine learning and data science.
• Proficient in Python and ML libraries (scikit-learn, pandas, Hugging Face Transformers, etc.).

Generative AI & LLMs

• Lead, Design, fine-tune, and deploy Large Language Models (LLMs) using platforms such as AWS Bedrock and open-source model hubs.
• Build and manage autonomous AI agents using frameworks like LangGraph, Crew AI, Phidata, AutoGen, or AWS Bedrock Agents.
• Implement Retrieval-Augmented Generation (RAG) pipelines with vector databases (e.g., Pinecone, FAISS, PGVector) to enhance contextual responses.
• Conduct LLM evaluations using prompt engineering techniques and custom fine-tuning to optimize performance for business use cases.
• Evaluate model performance using appropriate metrics and optimize for accuracy, efficiency, and scalability.
• Stay updated with the latest research in Gen AI and integrate relevant innovations into ongoing projects.
• Contribute to model governance, interpretability, and responsible AI practices.

Programming & Software Engineering

• Write clean, modular, and well-documented Python code, leveraging machine learning libraries and agentic frameworks (e.g., LangGraph, AutoGen, Crew AI).
• Deploy AI agents on cloud platforms with a focus on user experience, including building lightweight front-end interfaces using tools like Streamlit or Gradio.
• Use Git for version control, collaborating through pull requests, code reviews, and CI/CD workflows.
• Adhere to software engineering best practices, including testing, code modularity, and documentation for maintainability and scalability.

Teamwork & Communication

• Collaborate with cross-functional teams including data engineers, product managers, and business stakeholders to deliver AI-driven solutions.
• Translate complex technical concepts into clear insights for both technical and non-technical audiences.
• Manage multiple projects simultaneously, ensuring timely delivery and high-quality outputs.

Must have - Data Science & NLP

• Develop and deploy supervised ML models including regression, classification, and time-series forecasting.
• Apply NLP techniques for text classification, sentiment analysis, and named entity recognition.
• Use vector embeddings for similarity search and information retrieval tasks.