Data Scientist- Gen AI and ML

Job Title : Data Scientist – GenAI & Machine Learning

Experience Required : 3+ Years

Location : Nagpur

About the Role :

We are seeking a data scientist with around 3 years of experience in applied machine learning, data analytics, and GenAI solutions. The ideal candidate will have a strong foundation in traditional ML along with hands-on exposure to LLMs (Large Language Models), Retrieval-Augmented Generation (RAG) architectures, and prompt engineering. You’ll work on end-to-end data projects — from data collection and model training to deploying AI-driven applications that enhance decision-making and automation.

Key Responsibilities :

Analyze large datasets to generate actionable business insights.

Design, train, and optimize ML and GenAI models for tasks such as text generation, summarization, classification, and recommendation.

Develop and maintain RAG pipelines, integrating vector databases and retrieval layers to improve model accuracy and contextual awareness.

Implement and fine-tune LLMs using frameworks like LangChain, LlamaIndex, or Hugging Face Transformers.

Build data pipelines and automation workflows for scalable model deployment.

Collaborate with engineering teams to operationalize AI models using cloud services (AWS SageMaker, Azure ML, GCP Vertex AI).

Perform exploratory data analysis (EDA), feature engineering, and model evaluation using statistical and ML methods.

Visualize data and insights through tools like Tableau, Power BI, or Plotly Dash.

Document experiments, performance metrics, and maintain reproducibility of models.

Stay updated on the latest developments in GenAI, LLMs, and applied ML research.

Required Skills and Qualifications :

Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, or a related field.

3+ years of experience as a Data Scientist, ML Engineer, or AI Researcher.

Strong proficiency in Python (pandas, numpy, scikit-learn, matplotlib, seaborn)

Solid understanding of machine learning algorithms, model evaluation, and data preprocessing.

Experience building or fine-tuning LLMs and implementing RAG pipelines.

Familiarity with GenAI frameworks (LangChain, LlamaIndex, OpenAI API, Hugging Face).

Experience with SQL and working with large, real-world datasets.

Exposure to cloud platforms (AWS, Azure, or GCP) and containerization (Docker, Kubernetes).

Experience with version control (Git) and collaborative workflows.

Preferred Qualifications :

Knowledge of vector databases (Pinecone, FAISS, Weaviate, ChromaDB).

Experience with MLOps tools (MLflow, DVC, Kubeflow).

Understanding of prompt engineering and context optimization for LLMs.

Experience deploying chatbots, Q&A systems, or document intelligence solutions.

Strong business understanding with the ability to connect AI outcomes to business impact.

Soft Skills :

Excellent analytical and problem-solving skills.

Strong written and verbal communication for explaining technical concepts to non-technical teams.

Ability to work independently and in cross-functional teams.

Curiosity and passion for emerging AI technologies.