Senior Data Scientist - Generative AI

Job Summary :

We are looking for an innovative Data Scientist with hands-on experience in Generative AI, Machine Learning, and Python to join our AI/ML team.

The ideal candidate will have a strong background in developing, fine-tuning, and deploying AI models using state-of-the-art frameworks, with a focus on Large Language Models (LLMs), prompt engineering, and deep learning.

Key Responsibilities :

- Design, develop, and deploy AI/ML and Generative AI models for real-world business applications.

- Build and fine-tune LLMs (GPT, Llama, Claude, etc.) for domain-specific tasks such as summarization, text generation, and question answering.

- Conduct data preprocessing, feature engineering, and model evaluation using Python and related ML libraries.

- Develop end-to-end data pipelines for training and serving models using cloud or on-prem platforms.

- Implement prompt engineering and retrieval-augmented generation (RAG) techniques for improving model accuracy and relevance.

- Collaborate with data engineers and product teams to integrate models into scalable systems and APIs.

- Research and experiment with the latest trends in Generative AI, NLP, and deep learning.

- Communicate findings and model insights effectively through visualizations, reports, and presentations.

Required Skills & Experience :

- Strong programming skills in Python and proficiency in ML libraries (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch).

- Hands-on experience with Generative AI tools and frameworks (LangChain, Hugging Face Transformers, OpenAI API, etc.

- Experience with LLM fine-tuning, embeddings, and vector databases (FAISS, Pinecone, Chroma, etc.

- Strong understanding of NLP techniques, deep learning architectures, and model evaluation metrics.

- Exposure to cloud platforms (AWS, Azure, GCP) for model deployment and MLOps workflows.

- Experience working with version control tools (Git, GitHub) and data visualization libraries (Matplotlib, Plotly, Seaborn).

- Solid understanding of data structures, algorithms, and statistics